{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 生成数组的函数"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## arange"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`arange` 类似于**Python**中的 `range` 函数，只不过返回的不是列表，而是数组：\n",
    "\n",
    "    arange(start, stop=None, step=1, dtype=None)\n",
    "\n",
    "产生一个在区间 `[start, stop)` 之间，以 `step` 为间隔的数组，如果只输入一个参数，则默认从 `0` 开始，并以这个值为结束："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 2, 3])"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "np.arange(4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "与 `range` 不同， `arange` 允许非整数值输入，产生一个非整型的数组："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.        ,  0.78539816,  1.57079633,  2.35619449,  3.14159265,\n",
       "        3.92699082,  4.71238898,  5.49778714])"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.arange(0, 2 * np.pi, np.pi / 4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "数组的类型默认由参数 `start, stop, step` 来确定，也可以指定："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.        ,  0.78539819,  1.57079637,  2.3561945 ,  3.14159274,\n",
       "        3.92699099,  4.71238899,  5.49778748], dtype=float32)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.arange(0, 2 * np.pi, np.pi / 4, dtype=np.float32)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "由于存在精度问题，使用浮点数可能出现问题："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.5,  1.8,  2.1])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.arange(1.5, 2.1, 0.3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`stop` 的值 `2.1` 出现在了数组中，所以使用浮点数的时候需要注意。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## linspace"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "    linspace(start, stop, N)\n",
    "\n",
    "产生 `N` 个等距分布在 `[start, stop]`间的元素组成的数组，包括 `start, stop`。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.  ,  0.25,  0.5 ,  0.75,  1.  ])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.linspace(0, 1, 5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## logspace"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "    logspace(start, stop, N)\n",
    "\n",
    "产生 N 个对数等距分布的数组，默认以10为底："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  1.        ,   1.77827941,   3.16227766,   5.62341325,  10.        ])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.logspace(0, 1, 5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "产生的值为$\\left[10^0, 10^{0.25},10^{0.5},10^{0.75},10^1\\right]$。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## meshgrid"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "有时候需要在二维平面中生成一个网格，这时候可以使用 `meshgrid` 来完成这样的工作："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "x_ticks = np.linspace(-1, 1, 5)\n",
    "y_ticks = np.linspace(-1, 1, 5)\n",
    "\n",
    "x, y = np.meshgrid(x_ticks, y_ticks)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这里产生的 `x, y`如下："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-1. , -0.5,  0. ,  0.5,  1. ],\n",
       "       [-1. , -0.5,  0. ,  0.5,  1. ],\n",
       "       [-1. , -0.5,  0. ,  0.5,  1. ],\n",
       "       [-1. , -0.5,  0. ,  0.5,  1. ],\n",
       "       [-1. , -0.5,  0. ,  0.5,  1. ]])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-1. , -1. , -1. , -1. , -1. ],\n",
       "       [-0.5, -0.5, -0.5, -0.5, -0.5],\n",
       "       [ 0. ,  0. ,  0. ,  0. ,  0. ],\n",
       "       [ 0.5,  0.5,  0.5,  0.5,  0.5],\n",
       "       [ 1. ,  1. ,  1. ,  1. ,  1. ]])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`x` 对应网格的第一维，`y` 对应网格的第二维。\n",
    "\n",
    "图例："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Miniconda\\lib\\site-packages\\IPython\\kernel\\__main__.py:9: RuntimeWarning: invalid value encountered in divide\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x9ac1630>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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jRzNnzpyE3V+fJF0FXSVDhWybmprCZNuRn7Or2gUK2Xq9XiwWS5tleLqjj+D3\n+8MqZm310Z321WSuKLJFxnd2hdjbC91SSF6v1zJx6nDWf7ON6aeNBmD96p1MP3VUuO+tm/fzg/On\nA/C3F3/Fdxt2UTCkHwBX3zCPpiYnGzfs4bKrZlNeVsPEyUMxGPRs376902NOJNrbgrd1MHUyhLLB\nsVaxEh1z2mmn8eyzz2I2m6mvr+fxxx9n0aJFrT4rSRK33nory5cvZ/v27bz22mvs2LGj1TWNjY3c\ncsstfPDBB2zdupW33347YffSJ5MjumrpdrU+WGcXX1cyvLpCivFKbGgLinoZtC2oE+8HUyGeX/zi\nFwB4PD6GjS6g/EA1E2//EQAV5TVMmDwUgEMVdfj9ASZODR2wjRhdSHqGnZTUkGC7KIqMmVDEy899\nxIUXz0TUiHz6yQYkKcitt93KZ59+FtfxdwaxEFt7GWXtCX+fLMU0DQYD48aNQ6vV8j//8z9R7zMW\nsZtXX32VSy65JJyllpmZmbAx91lLtz3thUgEg0FcLlfYD9nZE/zOaBeorc5o2rkdfT4WqBMblHpn\nHSU2dIbUlfadTidGoxG73d4l8Z7uQBEbKRiSh1arobHewfvvfs3EodfjdHr453MfUV/XzKYNu0lL\nt4W/S5fTQ11dE99+tRWPJ3TId8fdP2bpm19ywzX/w9DRg8nOy0TUiKxft77PajEIghA1XEuJtOmu\nVdzb3RfRXlhtrc9oYjeRLojdu3dTX1/P6aefzuTJk/nnPxPnfuqzpAtHy6O3BTXZyrJMSkpKl07w\nYyERtehNV4mqIyjRFQ6HA61WG/eMOHX7SsZdIhJBOoLit9TqNEydOZrXX/wIURTYf6COeVf+AJ8v\nwP4DtUwfs4Dn/v4h+YOOqod9v2kPKak2rDYzH32wGoCpM0ahN+owW038/vHbOVRWzaU/DQXR33ff\nfT16b4lEpC80FuH4yAgB9TrvzdaxmnR9Pl84gy4aYrkPv9/Pd999x4cffshHH33EH/7wB3bv3h23\n8arRp0m3rVCuSLJVDn26Gi7VkXZBPBTG2usjsmJDVxIbOmrf5XK1aj9WMo932B7Aj34UciNkZIWi\nEx787XPkDurH3959CIvNzMCifJ7/5K/M/9VP2LCmhKLhR4VLNq0rITM3gzMvPI3nn/oAALfLi9Ph\nRqPTMWhIfyw2M/Yj7ofHHnusV0QLJBLtWcXRUnuVjEXFddHb5yQeYjcDBgzgBz/4ASaTiYyMDGbN\nmsXmzZsyyjejAAAgAElEQVQTMt4+S7pqQlAWRWRsqkK23Y0SaEuMxuFwxM0qjNaHLMvdcot0BPV8\nKTuBrrYfCAR46qmnuezKn/D444+zatUqmpubuzSuL7/8EnuaDUdTC2+89DGWFBujJw8HYPt3JRSP\nComQXHr9DxG1Iu+/+QU1VQ0AfPvVVkZPHsaNv76anVtLObDvEJ99vB6LzUx1ZS2BQIA555zCd6u3\nYUsJhdI1NDR0aAEmAsfzsKotq1jtu1cOgtuKmz2eZBwp62i329u8Vi124/P5eOONN7jgggtaXXPh\nhRfy1VdfIUkSLpeLNWvWMHLkyISMvc+SLhz16yoHZIkWvlEOL5QECq1Wm5DUYHXyhPrl0V2yVb+c\nlKgKJV64O+1v3bqVgQVF/O7e+1hbYeaxF5Zx8aVXUlA4hMuvvJq33347Zr0Dr9eL2Wriml9cgcvp\nYcKsiVhTrBSNDIWIHdhbwdDRIdJ1Olx43D4GDC3g7tufAmDT+l2cft4MrHYzBUMHsOT55bz9ymdM\nPn0yKRkpLHvzc+acO509Ow5w+nmhiIebbrqpXQswMkb0REnxjQYlQkCj0aDVatsUvHG5XLhcroSK\nAbWHSNLtrtjN8OHDmTdvHmPHjmXatGnceOONCSPdPhm9AK0tw+bm5oSXkwFwOp34/f5ORT50pg8l\nY8ntdocr+cZLNEaZL6X8uyAIbRbj7AyeeOIJ/vinhzEMOgtTwx4atryDIIoY0grInvkLvt2zgo9u\n/Bl6vY75113HzxfczKBBg9ps76c//Slej4/Na7aSlpXGXf/4PTfNuIaCoaGDkKa6ZgYNDW0N95cc\nxJZi5d4X7uPGU6/j9Zc+xuPyMunUsQDMX3QV/33bX/B6fDyz4kns6Sm8/9onPP32H3E0tTByXBGf\nfvAN33z7Tat56kjyUBElihS+6W55nN4ENanFMic9LZGpJveO3AsA55xzzjFiODfffHOr/y9atOiY\ncLNEoM9aul6vl8bGRmRZxmw2J8SyhaP+TgWJEqMJBALhLW578bzd6UOxTEwmU1za//szz3DfAw/i\ndrtxH96ELq0IQdRgH3wGAVcd5f9ZTNOOf5MyeA45sx/gzc/2Mnb8ZH4w9zxKSkqitrls2TJSM1L4\n9rMNTJs3E4CWRgeFQwcC4GhqCf9cuusgtjQ79jQ7l916JXff/hQpqkiG2fNOQavTYk2x0r+wP6fO\nm86+XeXoDTrGTR3Jzu/34vP6kfyhuW8LXU3x7S1b8UQgck6Oh0SmWuzmeGSjPfPMM0yYMIEJEyZQ\nWFjIGWecEdPn+izpiqIYJo54EqCCyMM4pVR2vMlWCTHzer3he4qs5tsdKL5nRZWts1EVbWHBLbdw\nxx2LyDntNwyc+2c0OhtNO95Ho7dgK5jFgLP/hAAIWgOOA1/jOPAVrrpS9LYc9jpymX362Zx3/gWt\nFL8UF0RDbSNanY7Bo4ZwsKQ0pIORmcKhsiqCkkR2XiiGctfW/WTlZwNw6YLLSE23k52X1Wqcg0cU\nYLSYARgxcTg+j49tG3fxgx+dxvqvvmfslGEEgzK33HJLp+egoxTfjlKelbja3ojuCN7EIgYUmX2o\nvKBiJeJI98LxUBi7+eab2bhxI+vWrWPAgAHceeedMX2uz5KuXq8PJxwkQowm8jAu3v1ExsJaraHT\n9Hg9hOqIB61Wi1arjVvyxD//+U/eeOs9TBnFVK78I7Vb38JVs5OMkZdhy5tE+ae/58Cyhejt+RTM\nfZys8dfTtHs5nrp92Aadgb3ofKwjruarr75h3rk/ZNGvFlNfX8/cuXMxW01IgZAu78Chg9j81Ub6\nF/ZDEATWrfyOfgNzw/dQsmUPxWOKw+NKz81k784D+Lz+8O9Kd5VRXVGN3+dHo9Uwec4kXn3mPWae\nOZmaw/Wc+cMZGE0GXn/9tWPusyvoTMqz1+sN/9xZ0ulL6IzGQqzKY2rSPd5iNwsXLuTMM8/kvPPO\ni+n6PuvTVRBPoRjFnxrNPxzPWFiXy3VMvbN4bUEVKUev19vK9xyP7Zwsyzz77LMs/MWdZE2Yj23A\ndFoqN1C9/u8IogatLZ+UIfPwtdTgqt2Bt7GUht3/xpA2GFmWSB08l/ptr+Mo/Qyfs4asUVdiyp7I\nO5+8xwsvjsTvdaE36Enrl0VzTT0Digfy3j+WUnQkWuH7dTspGlkQHs/BvRX8eNG14f9XlVej0WpZ\n8d4qzr38DOqqG2hqcGCymdn0zRamzJnErPNm8tyDL5CTl4nVbuG9V1YQDAbRG9uO84wHopVS9/v9\n+P3+sHsiWp0ytZ+4J63inhK86ar/XD3G40m6L774ImVlZTz11FMxf6bPWrpqJ393QnrUqlyKGE00\n/3B3yT3RUQ/xDP+K1rbX62XNmjX85rf3YB8wg5pNz1O17kkad76DJWsE6cUXULX2r5R99huc1dsZ\nMPM+csYvoHnfpxxe8xipBWeRXvwjBs5+hICrAYIB3E0HEfU2/P4AEgYAfF4fY885E4vdislq5lBp\nBcPGhiQc9+86SLESudDiwtnsZPjkUCqns9mJu8XF1EvO5aXHQ3nzW9buwJ6eQv7IoXz5768AmDx7\nInXVDfzzyaU4HS4OlFaBIOBxeXnssce6PVedgUKkbW3F4VgFsuNVGqenEKv/HKC2tpYxY8awcuVK\nXn31Vd5++2127959zLzEInYDsG7dOrRaLUuXLo1prBs2bODRRx/tdPZanyVdBV3VulWHTUWqckVD\nd8V1Okps6I4gTSzhX11tX/E5l5eXc+55F6DJmEzm6GvJn3kvrurt+FpqsObPIaVgLrkTf4HfWYOo\n0eBp3I85aww6kx29MZPG/Suo3vwPGvZ/DIJAv3G34asr4eCnv6C5fDUEQ1J99uwMgsEg+UWhaIXm\nuiZ2bdnLoqvv58DuMras2U5TfTMHdpVhSbGGyelASSlmu5W5P/8vqitr2PZdCd+t/p7MwoHMueZi\nvvrPNwSDQWypNgpHFPD4H15kyhUXotXrGXF66MCup7PT2kplVUgnlqyyrvpEuzK24wm1r1iZh4yM\nDN59913y8vIwmUwsWbKEyy67rNXnYhG7Ua5bvHgx8+bNi3kOn3zySRoaGjj99NOZMGECN910U0yf\n67Puha5auurDDUEQsFgsMR1cdZa0FMvT6/WG9RFisTpjXexdvY9Yoa54rNVquW7+TYjmQTSXrULy\nNmHMGAVBP2mDzqZq09NYsifgadhF6oDZ6CwDqN32MvW73iIoBRg0478JuOup2vp3fO71pA++AHPG\nSIxT76F01Z2ADLILUaNh6qXns2/DFsaMG8qGz9fhanGxdk0J+RPG4Zdkdu0+xKVTb2DK7AnYUm3h\n8ZbuLMWSloJWr6dg4liWPPku+0oOMumS8xg+YyIAOzfuYuSk4VjtVgxWC2fc9BO+WbKUoTMm8/3H\nXxJsJ4LheEPJKlNDvQ1vyz2hDtnqTSTaHSjPoUajoaioCJ/Px3333RdVpCYWsRuAv/3tb1x66aWs\nW7cu5nE8//zzXRp/n7d0OyNG4/P5WonRdCZSoDP9dCWxoTMPhHII53K5Yr6PzogDOZ3OVpl2l19x\nFTv2HCJn3G0MmHYvvuZyarctIbXwh6QP+REDpv4OV/UWJJ8Lc+Zk7P1mkD1yPgGvA+QAzppN6Cx5\nyEE/5pQhNOz/gMqNf+HwlicxmHPpP24xwYCEzmQgb3gxzZVVtDS18D+3PIjP62f+my9w+i9/huT3\nc91r/+D0RQtZ+8VG9CZDeNx7tu4lY2B/AC66awFffbyW8v0VTD4/FMaTXTiQL/+9iqb6Jrau3YYU\nkNCbTOQUF1JTWh5u58EHH4z5ezjeiDVSoCsC6b3N0o2EemwtLS1tRi/EInZTUVHBe++9x4IFC45p\nOxE4KUhXEaNRSKorYVMd9RO5zW/LN9ydPtSpx7Gqi8UKdcqxIAhh/YWXXnqZb1ZvoKWxgqrvn0Fj\nSEMOuDHaBtGw731qd72Jq74EkEnNm0Xlxv+lesdL1Ox8mcyC88kachW1Ja9xYNUdIBroN+o2Bk66\nF8lTj7thN8aU4dSX/it0f/4AucMG42pqYuXST8mbMhV7bjaCIFC+aSumFDsanY7R555FRlERFXvL\nWfdZyDLZvWU3BeNDGruZA/LIHNAPk8WEJTWUHjrj8vNY+f4qPl26Elt2JnJQ5uDm7QyfNY3d324g\np6gAoF2fX7yRCGLryCcaTSC9N6X3xoLIeVN2Y9EQy/zefvvtPPTQQ+HnL9H332dJV+1eaE+Mprm5\nuZUYTVdJqq1+FAs6FqHyrvYRGf7VlUO49savVIRQLHPlAG7p0qXc/stFZI9ayIBJ9+B3Hqb0i9vR\n6Oz0H3sn/cf8Esfhb6nd9QYZhZeSUXgJ/cctwlG1nqDkx5AyDFv2VNIHXYgkeZC8DTSUf4Qg6gl4\nG0nJnkHzoS9xN4V8bKJGE6pf5vIw/pqrMWekk14QSoSo2LKN1P554XE3VlQyaNZp/HnhIzTWNlK5\nt5wRMyeH/z7yjBn4fEd9nJN/eAZOh5NXH3+dkT88lwGTxrNu6YcUnTKJ+vLDjJgzHVF7NM31RDuo\nUqzijkRvlPRe5f+9cS7UpNvRuGIRu9mwYQNXXnklhYWFvPPOO/z85z/n/fffj//Aj6DPki60ramr\nbL/VFmF3JQqj9aPWzjWbzXFPbIhmfcarbLr6ZRGtIkR5eTk/W3AbPp+Pun1vozWmY0wZCgh4XYep\n2/8eemt/RMBg7kfd/reoK30fZ+0mREFDWu5sKrf8hcqtT1JX+i9yh1xLbtF8mipXUrrmLkSNDb0p\nH1PqRDgyr1mFA3jvwcfR2exMnn8tDftLyS4ORS7U7N5LdlFIfyEYkGipa+C0OxZiH1TA76+9FxmZ\nfkOPlvCpLNlPwC9Rtn0PEDpwzRiYh8ftZcqPL6V49gz2b/ie/qOG4ne7yRzUH50h5K4YM2YM11xz\nDa+88go7duzA5XL1qUq+saIt0RuTyRS+JloZpd44F209E7GI3ezbt4/9+/ezf/9+Lr30Up5++ulj\nrokn+uxBmgI1GUqSFJalUxIO4i1EA60rNphMprht8dXbm/ZihrvatnLgqIxfSaGOTJqor6/nzLPm\nYsqYTXrxJKpK/sGB1b9C8nsZOOZXBIM+Du9+lqZDKzFa8ug/8k7czXs4vPsfSAEvmYMuxWgZgLNp\nL66G7wGBw/tehmAAQWdC0Bvx++qo3r8k3KfWbEZnMLB39XdkjQoJjbhqa8goCPnjGisOUTA1dCDW\ndOgwOoMBo83K+X95mCU/ugKTzdrqfit27sGUkc66Dz5j4KhQAsWQyWOoLa9Cq9czaMokPv3zEyAI\n9B85lIptu5D8oQiKyspKKg9X88F/PgY5CNLRZAsEAb1Ox/nnn8/06dOZM2cOxcXFJ8xBlfoe1Os6\nUmdBcUUo7oyerFQRaem215da7EaSJK6//vqw2A0cq7/QE+jTpKtWGVPKgSs54InwlcmyjMPhOCax\nIZ7w+Xz4fL64C95AaIG2tLTg9/sxm81RXxaBQIDLLr+KgwdKMVq8mDOmklF4ORVbH0MQBRoqPyZ7\nyLWYbINxNu7A7TjAvg13E5QcCBodaERqD74FAiBq0Kb2J9BchSBqQKNDa03HPHg6zVv+jcaYTqCl\nFmQZo91G6XffozEayRwaIklfi5O0AaHDMXeTg/SBoW1h3YEydEdSe/VmMwWnz2bvJ5/h83jRGw14\nXW4ctQ3M/M1drH/yCX706xsRRZHSzSX43G7cTc2k9MvBYLWw47NvGDFnBt/9+2MGjh9J6cZtBP1+\ndJmFBBoqSJ1yBd7qPbhK14EUQNAa8UkSS5cuPRrPqTUcIecAOTnZLFq0iKuuugqbzdbu+uhLh1Xq\nRAZlN6cYCEpKszp7TE3CajKOB9Tz1tLSEq523RZiEbtR8MILL8RljO2hT7sXFElHIO7bbzWULVYg\nEEiYnKPiO/P5fHEXvFHCiRQyT01NjfrCkGWZSy65nO0ltRSOexC9KY/SDb+nYutfyOh/Dmn9LsBR\nt5G9axfiqNtIUPIg6PQEpWYEbaiYJLKExpaFdegsRI2egKMG5CDpM+eTPfdONNYsmjd/ALJA5rm/\nAVnGlJmJv6UFg82KKTOL9MJBoTE7naQdIVq/y0X6EQKuP1iOMfXoabXk84MgsGbpcgAO7dqP0WZh\n8FlnIAUkSjfvwOfxUrFzD8aUFA6sC+k9FM6YxsZ/f8KQUybSdLiGkbOno9Pr0JvN+Kt3gyzh2L4C\nd9kWtPZcBl7/Elln3oYgCJgGTkCXmgcICIKIIGhAEKiqquJXd91N/sBBpGTmYk9JJSsri4ULF+L1\nenvVlrwtxPoyiDXlOZExxR1p6fZG9GnSdTqd4Z/jLUYDxyY2iKIYd1JXH/ZpNJpW2UjdhTpLDUCn\n07U5flmW+fWv7+KTFStobthPY+0avK465KAXOeintmIZ9RVLQaNBMKcjaPQgCICIechMLEWnIgA6\ney5BdxOCRo9hwHhErQFj3mjqv34Bd9kWfLUHMOVPwDJ4Ooff+BUak4niiy/F2+Jk8E+uI+BsIXXQ\nQBr2lyJqtZhS7LibmvF7fdj75QBQvXsfqfn9w2Ov27uf9HET+fjvS5D8ASp27sGQmoooiqQVD2Xt\ne59SumkHRpuNjNHj2L0ylJ02ZOY0Kkv2kltciByUMaXYkINB/F4vgs5E/4seRtRbQJaQmqsoe/ln\nVH/yFzSWdNJOuZqUiZcgaPVknbWQ9NPmI+iMiKYUBGQQRITQxOL1ennxxRfJyu1PamYu9pQULr74\nYkpKSvpEtEBnEak+Fk2TN5rOQqzRE71Jd6Er6NPuBZvNFt7WJEL0Rp3YoLgW4gW1/1lxVahfIt2B\nWjdXo9Fgt9vDFkdb1//XNdew9N1lBIMaBI1EQ/Xy0OLWGZEDPowDxqKzZdOy6wvwOUGjpf8lDxFw\n1lLz+dPI3hYMuSPo98Pf4674nqqP/wySn4xTb8RWPBt3xRaqPvkzshQgfdo16KyZtOz+HAFo2F2C\nPiWVQRdeyq7nnyF14ED2fraSlLxQGfWyjVuwZqQjHvFr1+zZT+Gc2eHxN5VXcNqv7mbNXXfw3X8+\np3TLTlIKQ+nCo6+6glUPPIDBbMSUl8/gCy5gzX33IssyAyeNx9XQiM/lJiUni/cefByf24PGoEfy\nuhEMdvwNZeSevRhjznAOf/wn/I5qtMZUKt++C0HUIGiNtOz4HL+jFlFvJv+qxwi4Gql8cxH2Mecg\niCJNmz9ElrwgS8iyCIKGFStWsGLFCkCDKMJpp53KCy+8gN1uP+5VfBMVytaezoK6orGisxDpoojm\nxz1eCmPdQZ8m3VjCxjqD9g6w4ilIo2itRvM/d7cPddl0dZZaNL3YlpYWLrnkEr744ovQLzR6IICM\nLpSWK0mYi09D1Btx7FyJh20gB8k+YyGuA+upfOcuNLYsgh4nmTNvoGHDG5S9dhvWYaeD5Mc+9AfU\nrfo/JFcD+vRBIAcx542lcukisn9wF8gyQb+fw+vXkzZ6HM7ygwiigDE1hZqdu0gvDImdV36/nfRB\nRwPcmyoP02/cGADcDY3IgQC2QYUUXnIl//nbS2gNOoovvQKA/GlTETQavn5zGcOvnU/OxEnIcpCa\n3fvIHjqElLx+vPDz39J4uBrZaMGUmom7shxRq6HszYUYMgow9RtFwNOMp7qEfnPvxZhVROXyPyAI\nItbCGTj2rcLfcAAQOPD89SAICKJIoLmagKsRORig/+WPgiBS+c5dmAZNRtDoce5bA0EJWaPji1Xf\nMHhw6EWRm5vLO++8Q2FhYUJ9o8cbyktFsYwVqP3EajJW7l/5vbKL62uWbp92L8SLdNWJDW2J3sSj\nD/VWP5r/uTsPU7Sy6Wo3hTJ+SZK46KKLMBpNZGZmhghXo0M0WEJnX+ZUkGW0thxMA8bi2reagNuB\naE5Ha7QjiFocOz8lY87PSZv6YwLNhxGNFiyF08m/9DH0Kf1p2vA2qWMvIWPyT8g9czGNG9+l6uNH\nSBt3BTmz7yR19EUcXvb70LwEg0heLynFw6nbuAFbXh6CINB48CAajYaN73xAyaer0Og0SH4/Ppcb\nr9NF7qhQGmfDgYPojmT8Dbn0CjweL7UHKhh46szwvacPG07A56Pw3HMBMOf2Y+/X3wIweMY0Knfs\npvj23xF0uxhw2dVojUYEQQR/C77afRx49QbK3vklupR89BmD8TUfxltTQua0+diK5hBw1ZMy8jwK\nf/IytsGnoTFYSBtzEZKzCe/hEkStnorXf0nlW78GwFe9H/fBzRDwYhowFnPRdBBEREsGoimFw9W1\nzJw1h7y8PEaPHk11dXXU0K1ExdAeb3eHkvLcnntCkiQuvPBCbrvtNl599VV+85vf8MYbb0TdjXYk\nePPKK68wbtw4xo4dy8yZM9myZUtC769Pk66C7ojFdDaxobP9qJMPlPptbaUFd+U+gsFgTGXTlyxZ\nQnZ2NhaLheXLlwMyaPSIRhuCIKKx5aJNH4jsaUFjsCL7nKRN+wlZc+/Ac2A9squO7LN+Tf7FjxJw\nNlD28k3Ur3mF9Ak/Rm/vT9lbC5G8TgIt1WhMqTRtWYq7aiem3FGYc4YBAt6qbaEDz5HnhfoXBORg\nEFGrw1ZYSGPJDtIKCqjbvZeG/aXsW72Ob175F8119ZRv2cFTP/wJa195G4PVgnjkO2ooPYjuyEGK\nKIrkzDgNrUGPOSM9fO+Dzz4TUadDZwpFPOTNPI1dn38JhFwXskZH5ozZiFodghDK2JL8fgSNhsIL\n/k7GuP8Cv4dA82EOvjafivcXozWlEXDW0lK+CcnVQOroC5HlIM4Dq8mc+lNSx1xI0OfEOngGBT95\nnpQxP0RjtJFz1q8xF0xF9ruxDjsTyePGtftrBEEm6Gok6PeEokCOhPfV1NQwauwEsnNyufjii8Ou\nqI4yy7pLnL3NmlbHFAuCgNFoZMWKFdx6663MnTsXk8nEG2+8cUwx1FgEbwYPHsyXX37Jli1buOee\ne2IWrukqTlrS7WxiQ1uJGG0hUsUs1rTgzrSvJE60VTa9paWFwYMHYzQaWfDzW4/8VgSNHkEXutaQ\nO4z0U68j0FSBv2YvurSB5F/5BNaiWRx697dU/+d/sAyciq1oDoeW3UvAVU/2nIUEvQ4EUYO1YDr9\nzvwN1ryxVLzzSyR3E/nnPkL62Eup+vQh6je9ibuqhPwzH8Bbu5fqLx+jZf8qALQmExqDAVkOYhtU\niLPsIJ7GRv614DYCAYniex5j9GNL0JqsDL7zv0k/5wrWvPIWgiiGxWlq9+zFnHs0Uy1zzHhkBOr3\n7An/rrmsAlmG2m1bARhy4UXU7iulYss26koPIAf8eGuqSB07kYZN69BZ7YhGM7IkIcsSnrpdmNIL\nKDj/afpNXwRBCb01l6qVf6F65f8iiDqqVvyR8veO1NcSNbQc3IC/qYL0yT8m6HPj2PkJGTNvwpAz\nHOfer0gZdxFZs34GsoQhu5hB17+KffQ5iBodmbNvDh1Mag2IRlsoHE2jY/Xqb0lLzyAjI4OdO3e2\nmVnWnUOqvgDFpyuKIoFAgNNPP517772XpUuX0r9//1bXqgVvdDpdWPBGjenTp4f9wtOmTaO8vJxE\nok+TblfcC+poAWUb3pnkhlj6UQjd4/FgsViw2+0xhX/Fqi7WVtqugk2bNmEyW8jMzKTyUBWIGgSD\nFQQNHPEJmgdPJ+f83+Gt3kP9Vy+gseaQf/lfkSUv5W/chil/PII2tM0WNDoyT5lPxriLqfrPf1P5\n73uxFZyKfdA0Kj/8LZLfjXnQ9BA5BEPxqvah55A26iKatv0b++AzMaTkk3f6vbirdlDzzd8BCPr9\n6AcWEfT5Mefm4WuopWrrNnKu+jlIAYy5oQdIcjsx5uaTd9GP0RcMxedys/rpZwGo3b2XlKKh4Xtv\n2r+XYDDIjn8dTeM8vHEzaHSUH/FdG9PSMKaksOz3D2IeMhJLYTGVy98jY+oMmku2kzZxKpoj2WlV\na57CXbEe25B5CIKAo+xrTBmDyZ2+iP5z7kNAJmv8T7HkTkVyN6I1plL3zT+oXvkXZMlP2dsLKX3l\nepChftWTlC25jqDfg7PkUw6+fB3++jL8DeUcePE6HDs/BUFD7Tcv49r/LYhatPbckOUb8KJN6w+C\nhqAscOrsOdjtdh588MEOhW+UNRmrLm9vjh+OHGtHPt1YBG/UeO655zj3iBsqUejTpKsgFnnHaGIx\nnU1u6OjajvyqsbTfFql3lLYLobe60WjilFNOCWXWiho09mwIBpH9LgSNFuvQ08g+dzHeql0c/uAB\ngn4v6dOuJeisoWHdq/T/0cMY0gdwePmDGDOK6H/ugzgPrKFuzYtYh52NqDcj+z3Yh84jfdINmDKL\nqVy2mKpVj5M+8lJMaQUcWnFPSPXfWY2o0dNSupKArwWdJQt7wazweIN+P7ax0zFmZ9NYsgNPQwN5\nP70T08AiRKMJjcmMr6EeORBAnxGqfSY1NpB53lVsffd9dn3yKY1lZWSOGx9us6FkJykTZ7Dv408I\neEMVB+p27yLnvMso/2JleH5TiofRfKiKgT+9lbSpp1G/bjWpYyfiq6slffK0UHIH4Dq0ESngxdIv\nlA3nPvwdtsIfAFC/7XWseeOx9p+CxpiOqNGRf+aD9J9zPwIwcO4jDDj7IUSNlsxJ15F1ykIQRNJG\nXkTGlBsBgZTh88iasQBRELAVzSbr1JsRghKm/AmkT7mKgKMGjTkVY/5YJEctICNodSiP7kMPPYTd\nbuf+++8/Zi3FossbLcW3L1jEsYaMdeb5/vzzz3n++ecTLnrUp0lXmdD2hMzjWbGhLVJU+ujIr9rV\n9hUyV7tC1JZzaWkpRqORWbNmgSACApqUfhCUCTrrEbQ6TP1Hk33OYjyHd1O17CECzVVYB01FkINI\nHgd5Fz2Cr2Yv5W/9AlfFNkwZQ/DW7kY0WOl39j049qykbOntaPUW0oadT9XKPyEF3GSecgtBnxtB\nhrcRA6oAACAASURBVNSieWRNuQ1kgUOf3ENz6dfkzbgHU8YwDn1+H353A417PgZNaOzGAYPx11Ri\n7pfHd3+4B1kKkjrjLJwl32PICoWLNe/YhC4tA+GIJR9ocWAfPYX+Nyzm8z/9Ga+jhczRY8Nz4Sjd\nT+YZF6AxWzm4ahWOikoA+l3yU/wuF44DBwDImTARQW/AXFBMytgpeKqrMGbnojFbkNweAi0taFPS\nAAj6vdRtfpG6Hf86QsATQmWRandiKzgr1O/eZaQMOQtBEKnb+iqW3FHorDk4Sr9EZ07HOnA6vqYy\nRI2elOHnEXDXA5A29hL8jmpAJn3K1fgay5GDAWzDTsd58DuC7iYMOcVIXhey5MWQU4yhX+gQUdCb\nQxEnWiOPPvoodrs9nN7a3hprr4KvUiJHkqSoCmTHG5FWeEekG4vgDcCWLVu48cYbef/990lLS4vv\noCPQp0lXQTSyirViQ3f6iewj3plqajI3GAzHuEL8fj9Wq5Xhw0cSMs0ENLYsELUEW2pBI6K155I9\nbzGSq5Hq/zxM0FmLzpqJIGowZA+n3w/upnnLv2ja+m9M/ccguRrR2XLIPeN3WPLGceg/d6Oz5mLM\nKkbyubAPOY+0ERdjyhxK1af30VTyIaJGi6AxULPpRUStgdwZv8LbcACdORu9JZvMsTciCHoqPvkt\nOlMuot4AgoB1zFQ8Zfto+H4LkhREa09F1OpwH9iNaUABAM7d2zH2O/qQSK4WDP0GkH7KGVgnzkLU\naVG+Eb/Lhb/FgW3kOOxTZ7Pt7aXUbN+Ozp6GKIoYcvIoXxU6QDu0bi2yFMBTeRBLYTFywI9j3y7S\nJkyhfv03GDKz0NnsIAhoTVkEmutpLHmfYMBL5Rf3cfjrhwkGJUS9Bb+zFk9TJbaBc0IhgdVbsQ0J\nWcPOg19iH3Y+giDQvGsZqSMvQA76aPr+LXSpA6j6+inqNywBBMre/DmNm5Yi+91Uf/ZXvJXfY8od\nRrCpikD9QSyF0yEo463cjtaShiz5QQ4iiEfX268W/wa73d4pMW61e8JoNKLT6dBqtZhMpmMUyGIp\nGtmT6Mi9EIvgzcGDB7n44otZsmQJRUVFiR7yiUe60UKz4lUrTC1IE62P7pKt0r6azNtK2509ezY2\nm51AIAAaDaIpJUS2rgaQJQS9iayzfoHelk718ocJNFcjaPTIsox1yCxyzlxE/foluKt3kjXrVhzb\nl+PY9w15p/+OoLeZuu9eJmPqTeisORx89xa89QfIHHUFtVteQnI3kjlpAXJQpv77d8gefyv9Jv8S\nx8GvcVZuwFm5Fo3eis9xGFftdkSNnoxRVxMMePF76gl63IgmC+bCYQQaqhE0GoxjTsWQG/K9eQ4d\nxDwopC7mOrgP08DQz+5DZSEStIUOPVInzgBRw9533wFCVq7WYkXU6sm77Hoa9u5lz8efoOsXajdt\n5tkc/GwFQb+fms2b0KRk0LhxDYJGg234GA795z0yJk/HsbuE9CnTkbxeNEYTAU8VOaMXIAoa+o35\nBZb0KXga9iNq9Bz66k8c/PgO5GCAQ1/9kfJPfoXkbcGx9yMqVz6Az1lHy95POPjhHfgc1dRuXELp\nW/PxexwIAR+BhgOIWgMZ467GkFaEwZ5L4ZUvY8oswpI/nn7z7ifobcFWfCqmglPwN5Yh6s3oswaH\nfL1yEEN2MYLRDhpd6HcInHnWXLKysqLGZ3cEJTkhWopvewLpPVG/LdLSVXZ/bUEteDNy5EiuuOKK\nsOCNsit44IEHaGhoYMGCBUyYMIGpU6cmZOzhMSW09QRDfZCmVMGNpzJXNCgnw4nqQ5Ikmpqa2izx\ns23bNiZNmgSEDrhkQQApgOxzhRIatGZSJ16M7G6g5uPHQg+hoAVBwJQ7gpTR53Po4wdJGXkeuWf/\nhsMf/TcyYMoeibt2DwFXPf1mLabiswfQpxWis+Xgrt2DOXssKYVn4W8+wKGvHqTfrHuRfE5AwO+s\nwp4/k6yRP6F6w/8RDEr0G/0zAp5qqr97ivw5j9C8fzl6Uw5e55GTYSmAPjefQIuDtAtvxr1jDZZB\nIStDcjRiPEKUvtpqMk6ZA0Dz1o3oM7LD37u7vBTBkkrJkhcpOOdcmkv3o7GGCFlrtmLIG0Tl2nUM\n+OltAOTMu4RDbz3Pwc8/RWMyY500h/o1X9Lv/MtJnXwq1R+9S8GPr8fXWE/auEnUfPkZQb8ftHoa\nyr5Ao7NgThuOyT6Y+tL3yR9/FzpTJgdWL8aWNwudKYvaPW9hShuOVpuNq2YtxtQhmNLH4qj8Gmu/\nyaQNv4KaTU9jyhxG+qgrKf90MWnDf4gl/xTqNr1M5ik/w9tYhuvwNoy5Izjwxs0E/W68JYegZCUa\ncxrm7CJaDm5CZ8vCmDEAx/71yHIQZPmI1S+DHMDrk0lLS2PBggVx8VOqkxnU6CiZQZ1dBnDo0CG+\n/PJLGhoaqK6pYfXqNTQ1O9EbDNRWV+Hx+cnPz8dg0OFxu7jwh+cxYsQIRo8eTd6ROG41OjKoOhK8\nefbZZ3n22We7MzWdwglh6Spv1/aq+XYHyiFWIBDoclWIjtpX4i1lWW4zlnfIkCFMmhQS6ha0utD2\nUpEdFDWYC6diG3E6jWtfp3nnSkS9BX1KLlqjhX7z7sVbs5umLf+i37x7adq2jOrP/xdRZwIE0kZe\nQvbk66hZ938IWjPZU26mbv1zOA6sIWfiLTgPbcBVvY300f8FgkjZisXoTZnkjrqBuh2vEPA0YMs/\nFY3BjiAIWDJGY887HXNqMZVf/x5XzXayi28M6TUIIrIk0bD609D9zvkRgbrDGPOP6OV6XGGXQqDF\ngeHIz869OzHmDQrPh/vAHswjpqLN6Mf25/9B4+5dGHKPuiJyLvgJAOmnhEr2aIxG9BmZbHn6aXR5\n/8/ee4fZdVb3/p9319PPmXNm5kyRRmXUuyXLluWCLTcM2IDtAAGMaQmYJIR7SUi4+eWShAv4hgAX\nMLYx5GIbAgEMOLZx71WyLMnqbdSmt9Pb7vv3xz4jjeUmjPM8Mb/feh4/Hp2zz67v+93rXeu7vquX\nlg3vpda3B880Sa5Ygzk5hpJMoaXSWPkcTq1CqLsHbJPC0TtJdJ6NEILC4EPokSxquBWzOoRjV0nN\nvIhoZiWe06B98bWk5/0R+Batiz9Eas7bca0Kqd53oqgRzPIg8VkXYBSOYtXzxOa8jdyOn+JadYpb\nf8Lw/X+PrEXQtDiebZJZcw2dF/9PhKyQvfTvcFwP324gtCi1ge2AQI1lUCIpcKxA9UxSEc24/003\n3UQikXjFTrmvNh5/1wTzKxUz+L7PM888w+23385nPvMXzOldRLaji2XLV/Gp6/6c/33z3dz844d5\nbuMmJvS1HCrEGRjsx209iwPjgo3PPMnBccG3f/oUf/yha7hgw4U4jvOScuC3or2lPV3f9ymXy8cH\nSTwef/0f/Y42vaxWURRkWX5T5Ran7z8cDmOa5svAfGRkhDlz5gBSIKSiaPi+h1B1QKAms4hwkvrR\nFxCyilB1Eosuprz3QWKLL8Uc2MLYQ1+j/cIvMPbgV2k8+DXAx7XqtJ/xGbzGJOPPfYvut3+DRP4Q\nY098BTU5AyEUJFkn3LqM1kVXMb71Jnou+hci2ZWUjjxGvHsDsewaGvntjL7wDVLz3otnlpGVKOP7\n/432hR+ibdHHOPLM51H0DKP7voekh/F9kCMRcg/+CqUli5BkvEYVvasHzzJxG3VC2YAuNh2AGwNH\niS1dc/y+GENHSL3zfFIXXEn/1/4EPZUidf6JeF0o24UIRzCGj6Glg6aFydXnMHbvL+j6wOVorZ3I\n4SjlvdtJrlyLUFSK2zajJlMcvPEbCEXBmhxDqBq+bRJtC5adjcnNxDsCFkbh2D3E21YgyTq5I3ej\nR9tRI20UBx5HViPo8R5Kxx5G1mJoiVnk9vyMUGomQlYZ3/gthKwycP9f49kmkdYlhFuXYu3/Nd0X\n/iOVo0+jhA4Ral/E8ANfAqEwfOcXgpfazNVY1Ul8zyNzzscp73oApz5EfME51Ad34DYq4DeBU9bA\ntZorJNhw4aWcvf4MZsyYwQUXXEA2m/29QmO+7zM4OMi+ffvYsmULDzz4KJO5PP1H+xCSSuvMM8mP\n7kHRY3Ss/ypDG7+CrkYwTJfG5B6EpDK5/XZ81wHfI7/7DoQkI2kx6iMv4rs28xYs4q47f40syy8L\nmfxXpbe9mr2lQXcKaD3Pe1klyu9r07vhTgmVG4bxpr1dp+9/SgpvKkQy3c4//3w2btxIUNQgg2vj\new5CSEhaFKFFsPJD4PcjZJXk6iup7X0YY+hFMmf/CblnfkB03nkgq4zc+yWQZPB94rPOJdQyh9yW\nHzLjkusxJvcx9uRXaF/3WYqHHsU2qsw+73qGnr+eyZ3/l7YVn6A2/iKDj/9PXKNIqutt5A78jFjr\nSjLzP0j/pv/J2Is30zbrasKJXgZ2/Qux9rV4Tg0hqdhGHnwbEMiZLpzcECga2owgXus1auidPdQO\n7UGJxpF0HauQC+hiLQFgWoVJ9M6gfY/vedi5cSKL1qAkM4Tmr6K+exOzVp55/N7VjxwEz2fikXtI\nLAsAJ33ORYw/+BsiS9cCoHbNpbjlWVKrziC5fDX7vvnlQCoyliZ2+iXUngv6t0l6mLE93yfcsgij\nNk4mPgvf9zDLfbQuuCY43uQLxLsCIZ7ayBMkZpwH+FSGHkdLzqJ4+D4qg0/juRbHHvpr8CGSWYKe\nmE2p/0Gyaz/LxIs/INqxFKElKB64FyHJDN79V0hqhNY1H6G05z8Idy1DaZlFbdOPkENx8s/ciu8F\nK55K37MISUFICpIewXUM4KVj9tFHHuDRRx5CCBk9FML3XMKRGKefvobZs3uo1yqsWLGClpYWKpUK\nmUwG3/fp7+8/XpSzbdsOJibz5PMFhoaOIUkKLa3zyI0fJNa6nFj2ciTlJjILPohtlnCMpxCSoP/x\nL+B5DoQ9zPIWwpn5xGacw8TO24nNOBMplKZ86D4kLY4a60AYE7zrHRdx4w3fQdM0bNs+DrKO4/yn\nhBD/s+0tDbrA8Zs+leD6fd96J6t/ndx94vcFXc/zqNfrr7r/6efxEnFmKQBcJAUha8jhBE5lEmHV\ngrLIjkXo2fmUtv6KUPcK7MIA+Wf/FWSF6oFHEUoYPdWDZ1VpXXsdI098lUjnacRmrGH0ya/SecE/\nMnD/5+m//wtE0ouoF/poFPvIrryOwU1fIT7jHBKzLmF0y3eJtq4lPeu9WLUBRnfeQNdpf0UoMZvq\nxC702Gz06Exaey5nfM/38ZFItV+I5zsUR+4HRQ0SfYqKnGxH61mINdYPCJREC7XHf4ue7caulMg9\n/TBquvU4Xcyt16bFekcRqoqSzADQ+r6/oP+fthzn1wJUDuxE7ZhLcfNTeJaJpOk0jh5EqBr13c+T\nWLuB5LqLyd9zK7M/8TkicxZS3LqR9s/cwOh3Pk1o7ioqz90FnoNvW7jCpzyyCSGpjOz4Dp4bvCDz\nh39J4dg9mLUxpLHnqI1tolEZwazdR+7gbxCShu9a2MV+PNemc+mnMaqD1Cefp2vNXzK0+XqSPeeC\nkKhP7EJLdHPsPz6NpIZpXfEhCnt/SWLBZTiNElZ5FMco47tPEM4uRk12Uz74KC1nfJDaoeewJvrQ\n2ufhuxbWxLFgZSTJQSiq6fE2RyK+72E0PISQcDyTZ18Y4+GHH0VVIzz4+DGqxQOYRpFM+1LMRoFq\neZiW7BlYZoNacSdts96H5zXw/X5mLPsipYnNeN4+kMKM7L4Z8Bjf/SOEJBNumY8a7aYy/DTdZ/4t\npf7HsYefwTVLTOy4Fd9zqAw+jxCgp+agxdopH3uGiy+5lBu+83+OU9ggiOFu2rSJ8fHxt5zCGPyB\nxHTfjBjPFBhOp5idTP/6fZdgr1e2O8VeeNe73hUA7lSiUNHBs0FSUVPd+FYDt5ZHyAqyFkLrWkoj\n109xx73g+zSOvYBbLyCH0+C6tK37c/Bs4gsuBSFR3n83rSs/yMTzN5JcdCWe79P/wF/j+y4gke59\nD+2L3s/k7ltRw21k5r2bsa03Mrbt+0STS2nkd+DaNdrmfxSjdIyxPT+int9Hqu1sxg5+H89zSHZs\nQFYTeG6Dls6LKE88C0B05Qa8ahFt5jJ820DrnI2xfxtaWwdOuUDxmQep9e1h259eycC//yt2Mc/+\nr/0ttSMH8Rp19GwQajCG+5FCJ15KTnECIcuM3nmiBVDt4B4iqy9EhCIUtwUCN8VtG/GRKW9+HIDE\nuouwSwXM8RHG7rsDz7JQWjpQs3MwB/YgfB81EwC9Ywyiqjrpzncwa/mXCccXEEksIpY+D892UbUW\n9PBCPFdC1VvonP9pEm3nEIn3MGvVV1BD7SQ71hJtXUl9YiPxGRfgOSZG6Ri+UBl45Av4roOEjKJH\nSC+5CiFr2LUclb6HKO76NdEZa4jMOB0kBTXVQ+XQkwgEheduw84fIzpzJU5hEDs3gFAUJC2MP/Um\nmhprYvq0d/F9G9cuUS/uBN/C8wyKkzsw6jlkNUW94VGtDKOG2rAdmXp5D7Iaozy5mdzwPUiSSv+O\n6ykOP4CshGgUdoNvk13wUaLpZaihNLHsWVRHNyIkhaFN/0xt9Hli7SsACUnW6F7/RdRQEt9zwW1Q\nH93Ou99zJXf88ueEw+HjcWJFURBCcODAAb797W/zwAMP0NPTwxVXXMHTTz/9snn3emI3AJ/97GeZ\nP38+K1euZNu2bac0n38fe8uD7qkUSLyWTad/+b7/mhSzN6LxcCplu1N26NAhOjs7mzqrBA0bhYTv\nOseB1ymPghTEdmU9gmPUMQd3IFybUPsChKwQnbUWLdmJrOnEZ51J8cUfkzntGnIv/F/Sq6+lPr4b\nzzHRU7MYfPjvcBoFPLtB26KPkpn7DsZ33kys8xy0WBdj279HuHU5rlVDliN0LbqOWMsixvZ+D0VL\nkplzJdWxLbR0XEp6xuVIcpTxvh/hWmWsxgS+51McewLPqyO0MCIUxbdNWt/7BTyzhtY5G/PYXjzT\nYN/nP4g5MUby/I/Q87d3onXOJ7JsA0bZYtf/+HQgmdiMp5sj/UixE/xMa+gwUryN0rZnsXJj+I6D\nNTZEZOk56PNPZ+LhuwJN5D0vkrzwGmq7NuE7DpKioba0cfim/41nO8ipLNUtDxBZsp7GnucIzTsN\npvFgzUaOaCooxrCNYRLtbyPRug5Bg1THxWS63wFelVT7+UTi8zGr+4i1rg9+Wz1KtH09VmMSq5FD\nCbUw9PxX8V2L+sjzeK5B6+I/JjX33bi2iRbvYmLrvyKpEWQ9qHhLLHkPtWMbwXMo73sALdVNas0H\nQAoAtjG6H8+1EaqOEo7jOSY4FkKNBOLq0CwHV4L/v2Sw2oCP61o4VpVoeg2hSDeN8l5UvR1VS1DJ\nPYesxIgmF2A1BtAj3bT1fCAo+mg/g1kr/wnXqaNFOin0/5Z6aT9WY4KJfbcjyWFa530ARYsSaV2K\nJzSs2ii+5zD0zP/CtWskZ5+HaxksXNDLD39w8ys6PYqicM011/D1r3+dT37ykzz66KN85CMfob29\n/SWXcypiN/feey99fX0cPHiQW265heuuu+4UZ/Ybt7c86E7Z7wqI0wVpHMd5TfWvN3KMUynbnW7X\nXXcdy5cvb/6reQ6S1tyZGywTtQhCVlEjSXzPwbUMlGgKJRQjOnc95kQfevsCGuP7kZRwwIstDaEm\nu6gcuJdwxwomnvsuanImuV2/oJ47FPB2s2fQNv8qcgf+jWTPpSBpTO79MW1LP0m90MfAc18m1rIC\n16lSK+2lddYfY9ZGKQ49TmXsaYQQ1IpbEUKmfc61VAu7GNl/I3q0m9bZf0xu8D8COpvvYex9LihN\ndm18x0ZJZzEO78atVUhfeB1yKIbeFfRIc8t5Qj1LyP7xP5FY/34QgkNf/xs8x6Z+9CBa9kRNvXF0\nH3pnL2rbLEbv+hmNoWNIegglmSF18bVU9myjdmgfvuMQO/NyhKpTPxhI+IUXrKK8cwuxM95DdPHZ\n1Lc9SmjRGTj5EcLLz8UzqgFIAUghZCVKo3IQz3MIxXpxrCKWUSSaWoHjVLEaOWLp1VjGZPB5elXQ\n3sgPlvKjO7+L7zlM7L4VqzZJ69z30b7o0/iuTbzzDHL7fwq+y/AzX8f3bHou/DpOfQwkhZEH/x4l\n1kpm9bWAj1OZoLj154SzCxB6As82CM9cBULGLucIdy1FiaYALwgxIBNQyprjKhjZJw9eECq1/GZq\npb0gZAQ2jeox8G0ULUOtfBjPbeB7DuMDP8d1GlQmt3J4y1/hex6KEsJqjJHqOJfuZZ8FIaPFuskd\nugPXaVCb3ENjYgfxjrW0zL8ShIwSzWJM7CERFtz327vQm/oXJ8+r6QLmLS0tzJs3j6uvvpoFCxa8\nZNtTEbu56667uPbaa4FA7KZYLDI2NvaKc/TNsrc86P6uojdTYFgulzFNk1gsRjweP6WA/Kkew7bt\nl5TtvpbgTaFQIBKJntQQzwMECB8kFYSMbxsoya4ASOslor3rgknjWLiORbXvKZAkGoMv4pt1GmN7\nscrjNCb7qI/swSyNUBvaGlx/YZBY2wo0LUbnqs9SHXueUMsS1FCa8d3/SnbZp6iMPU956FnARyDI\nzr2W1u53MnHoNoQcon3uh8kd/TWOWaJr0V9jGZMUxx5DC7WTaj8Xsz5GS9d7CcfnMzWpfdvEKY6h\ndc2ncWgLSkuW3B034JZypC/8M2JLzsczq6iZIITgGZXjfzsTRwnPOwtjaJDD//K3NI4eQJ+9+Pgd\nswb60HuW0PLOPyP3+L1Udm9BRJuc3UwncqyFgdu+g5xoDUj/2TlUtgQCOJElaxCqRmLdVYTnn4Ez\nOYjWNQ9cFymSwK0W0LqbE9oLmCaliceJp09DCJni6MNEEr3ISoTiyMOE4z0oaoLc0G/RIlkqExuZ\nOPxveE6dsd03YRt50l3vomv+ZwGXRNfZFI7+hlBqNuM7f4hZHSOSWUYoPoPEzLMZ23ITjlEhlJiB\nkDVCrYvIbfsxSiSDjxwkFcujOKVh5FCC+tEXwPcItc+hMbQL16zhuy5yJI1Q5KCK7SXj/eQx7YFv\nAQpCyCh6K6ZRRJKjpNrfhmPlcO0SyfZzEJKO71q09VxFtGUNkqTRtfDPceygzVO9sIPh3TcGkpmN\nSTzXoHPZdYRTC/A9GyO/n/yBO1D0BBLgmkV+9rOfvGqV2fT5Vy6XXzOmeypiN6+0zf+vMnaKdiqA\nOB0Mw+Hw79z88fWOMSWqU6vVXlK2+2p2880309nZiee91OMQSvMN77kEAicaciiGU+gn1NaLHIpT\nO/A0IHAa5ePJNSWSQdJjyNEMSrQNSY0Qal2IUDQSvZchSTIt865ACJ9QelEgQTjyHC0zz2N85w20\nLf0Tarld2I0cWiRL4cg9tM18P+FYD6N9PyCZ3YCsxhk/fDu+G4hFS3IYRY3R2vN+CsP3YdaHKE8+\nh1Ai5Ad/PnVnTly0JBOauQRzYA9uOUf1+YfwPQ+9Yy5ONWAryMm2oN23WUNpgq49OYjeOZ+uj32X\n+tHDGINHCC8IhG5838eeGCQ0fy2hmYuRE60M3/EjlLae44cNLz+P6v5daDMWARA78woqLzwWhBy2\nPInvgTWwB33GYnyrgT0xQKj3NBo7n0RJtiFp4YCiJykc2f4ljOoxzMYw+aFfUSttx3VtcgO/oJLb\nhNmY4MiLf0u1sA3bLFAaewLXNWmb/RFaZ30EAaQ7LyY/fA+J9tXYRoF66SBG8Qj13EGiqV7aFn0E\nozxAdeh5jPwB0gvfg4cEvkfl0CPBiifZjW9XkfUoTqOCHGvFc0yErOC7NmZ+EKFoCFkh3L0E16gE\nHrvv4XvOtIEt8cpQ4OC5DezGcJBss/KUJp7FsStIcohGeR9G7RiSrFEYuZdK7nl8z2Zo7zew6kMk\n287E80ANtdC17PM4VgkhKYzsugmjuJ9Exxpcz0ENtRBuXY5v5vj+zTeybt26V50zcMLRKhaLrwm6\nb1Q58D+bgvb/CdB9NTB8swRpppftKoryuoI39XqdbEcHn/vc5046gASSGvAVZa3JWLCQJAXPsQCB\nOXkEzzZAktGz85DDSSQhQIBTmwAEvl3Hd23USAqreIxY91oqxx4h2ft2CgfvJL3o/eQP/prMog9R\nGd1IqHU1nutQGniMaGYZY7tuwXdsVC2BUTtMW8+HqFf6qJf20j7nY1TzOxg78itaZlyJY5Upjj3e\nTCitZGj/t1G0JK1zP4ZtFhk7dGtwbbICioqkhtCyczGO7QQge/5/A9dGSXViHNuBnGhFCAl77HCT\npRFwr916CTU9A0mL0PGBr4Gi0jgU7MMpjIMko2UCbm9yw0fwGjVCvSfUxxIXfhgkidDCgFIWXrIe\nz7YxDu+htuM51FQXtb1PI2QFvWc51WfvJLx0PcbhnYSXno1bLeBPCb74TRqWnKBWGcBzDDwfatUh\nPNcknFpNOHMWQkDXor8inFqNpqeItaykNPYQybYz8JEwqodolI8xsOXLSEKnZ8WXkCSZWOe5DG/7\nJkJIRFpX4ftglvsxJveSnL0hCB3ZFsb4XvT2xXiOgZAk3GoO37VQkp34novv2oSyi5AjGRqDO4+z\nGISsIYQcNBd9+Sg/6d8y4OF7FkJS8H2bULwXPTIPyyiSbFtPKnsJjt0glT2XzvmfRUg64XgvRmMC\nxyrgmEWGdlyPkHVSXReDLwi3LKRRHsRzGtiNHJXBpzhr3Vr+6I/+6BXnzJRNDy9UKpXXFKc5FbGb\nk7cZHBx8mSbvm21vedB9rfDC7wqGp3Ks6cc4lRY8J9u+fftIp9OUiqWXfynJAUvB98BzkWQVOZ7F\ntWrNWnsF3zHRs/NQ0jMwBnfj2QauUcG3TXzHwbPquEYZ16piFo6BrFEd3Ei4dRGVY48RbV9Otf8h\nYh2rKBy8g/ScSxnf+X20+CxKg49jFA8iKzG0cBftcz5KJbcZz7No7b6c8WM/xjImgKA2PxRfvDsh\neQAAIABJREFUQHrm1ZTGHsE2c6jhYEALNYMkh0nNuBqrdij4TFLQM/PwzDpC1XGrRdJrr8G1qsjR\nNEKSMYb3obYGSz3z2A6UVPbEvTbraE0WgVvNISSV/J23YI0PYg0dQQqfKIyJLDkHFO0l7AbfqIGk\n4BSDeJ0kSSiZbkZ//A2kUIzk6VfS2Pcsvu8TWbyexsGthOavwStPElqwFrcyiZJoDWLTeETSq0l0\nXoos60RSi2jpeR+yEiWSnE+8/Vzs6mGiLcsQkopR2kYssw7P8zDrg/hCY3DPV3BdC0VNo+kp0t2X\nYlaP4VhlJg78O3Zjks5ln8GuHEMA1aFNhNLzqAw/j+97yHoMPA9jdAe+5wYgKkAoIezCIFrrbPTO\nJTQGXsQuDAbdmTsWICkqcigejLVmdSC+FyRnpROSkSdsyiOW8H0PNZSlUdpHvbwDcCmNP01++LeA\nR2HkUUYOfheBwLWLWPUBUu1vI5m9CBCo4Q6KQw+B72CUjuIYeTLzriLReSa98xbyi5//7FXnzfHn\nOA10X8/TPRWxmyuuuILbb78dgI0bN5JKpchms6+0uzfN3vKgO2XTAXGK/lUqlRBCvCkKY9OP8UaS\ncBAIJK9atYrgtk+B9xSNRwHXCrwPST2ePHNreeRwEnO8DyWaITb3DIzhPTi5AYSiImkR0CIIRQt+\n0xQ8kWQdoeh4Vh2QqI/txjFKVEdexCgPUR3biVEeINd3D65dp5HfTzSxAFmO0DnvT6kVd+H7Hqn2\n9Ywf/iGJtnORpDCjfbcQz16MqmcoDPycULyXWHolY4e+T37oHsLpdZjl/TSKu5H1QANXCqfxHZP4\nnLch6WEm7/omwveI9KzGGN2L1hqU9toTR9A6gmIJc/ggWvtsAJxyDt91kBPNIonJfpRohlDnckZ/\n8A+YAweRoyc8HnsyiMlVnrzj+Gfm0V0IRaP2wn3HP4uu3IA5eIhwzxoi88/BM+s4uUHCvQHYStEW\npFgLTn4Ez6wHoQkpyPy7dh3f93GMIfTEyuA8G8fQk6uCDtXGEOHkalynjtWYRJLjjB++Bc9tUMu/\ngG2VaOnYQLr7vdhmiXBiAeNHfhqAo55FUSPUC/sx62MkO89CSBpG4TCeXSOUWYBnlpFCSYSsg2vj\n2fUm3cpG1iJY44ewxg8iZAU10Ua4ZyXm2EF818UxgkIi37ERUlPv2XOaL5SANhgwG6QT4xMHfAfb\nLCCEjKyE0cJdCElCkkMk2i5AURNIskas9Swcqwy+TzW/meLog8hKGLs+CkLQvuDjCBEwcyYP/JzK\nyHP84JYbCYVCrzl/TnaqKpXKayqMnYrYzTve8Q7mzp3LvHnz+NSnPsWNN974mufwZthbHnSne7rT\nO4S+Hj3r97GpJNxUT7XXS8LVajVSqRb+7M8+2/zkxOAJVKFohhYCwBXCR4m24tkmanomnm0iJBWn\nlqM2sAOh6KixNELRcY0y2I1m/JeggEJW8ewavmMiaWHwffRYFjXSDkIilJiH55gk2s9FSCqdvZ/E\n922S2YtxnQbVwoukOy9i8uhtJDsuw/UsBvd/E8cqgpCR5AiJ7isxqkeoFXcSTa8P4nVylEh6NbGO\niyiP3sdk380B8DcKqPEurMJRvEYFt1IAQI5msHJHjwOtWy2gNeOwdm4AtSPojmsc2YrSDDsAWGOH\nURMdtF/yVzi5MQoP/hQ1O/v4PbVG+pDDKZzCGObA/mAfB7cRal+IW5rAngiWk5FVG0CSiS69OPB8\nE1nq+zeipLJIkST17Y+gpDsp/PpbCFmhvuuJIEYqyRilHRjlffgI1EgPZvUwruugR2dTL27FdS2s\n+hHGD96E7zsUR+6mUT1GrHU9rXM/je87RNNryQ/djZAU+nd9Hc81mbn4b3GdIq5jUBy4n3jbKuql\nI8GYEUHSrDGxF19IuEY5iM2KZl5CVprP3kDICpKio3csCuQm+18Ez0OJtSKEQE1kgwIVPXYizCDE\nib99lyChOx3oZPAthKQG19cYRQt3o2pJSuOP4HkmqpaiPPEUQgmT6rwExzUJRWcSbVmFY1fB9xjb\nfwtC0snMeS+6HuPmm2/i9NNPf+1JN82mC5i/XnHEZZddxv79++nr6+OLX/wiEIjdTBe8ueGGG+jr\n62P79u2sXr36lM/jjdpbHnThhMrRlCjNf4bojeM4VKtVAHRdf92ealN23333kclkMIzGNFK6T8BO\nkAPvRATJDfyA1iOHM3hWFfCx8/2oiXYSK96F59iE2nsJz1yFXS8FCTY9ilD0Jh2IYLK47nEOpmdW\n8H0XxyziWBXCqflY9UGSHeswKntJtK4hP3wX6Y4NTPb/hLZZ11Aae4xoyxoQKhPHfookRzDrw8Q6\n30Gi8xLKI/cgSRrJzssoDd/DxJHbUEKd+G6NRn4renwhkdRSfLcatO8RgnDnMuqjgbcZ716HmuoO\n5AHr+eOermfWjhcieLUTzAVzYC9q6wmhG2usDy07H0lWad/w3/FNA6174fHvzYG9aIkuQm0LqTzx\nSwCMQy8SnXMmSrKL2taHgu0Ob0eoIayh3QBEetdR3x3o7YYXrKNwz81YgwdAidB22scQcgjfdfAd\nE4DKyG/xXYv84ZspDv4K37MY3fvPVEYeRJJ06qW9OE6dWPuFJGd9GIFHLHMW5fHH0MMdNEp7aJT3\nISsR9MgMYqmFWPVBbKtMKDIThIJRHcGuj5LquaS5+lGCl8+UZ+oHimJTyTDftfE9FzXdA3oMY2Qf\nbnUCIavEF1+IU51Ez8zBqReQ9Xjg9Qq5ubpqJtgk+eUc3uPjVsHzLPBdJFnHrA1gNsYQQkHV4lhm\nEYFAwqM4+hB4NkZ1gEpuM/HMSuJtZwVjH5/coV+yfMUirr766lMSSD+54nSKMvZWs7c86E7pLkzV\nYf+ujIRT2f/0rhDAKSXhPM/jG9/4Ju9971UEg6wZO4OmZzIFvEESTCg6khLEm53aOGqyGz09iyku\nZnn7fyCpIYyxPhpHX0BSQ7jVHJ5tNoFbNGNyBPG56ea7TRlGaBT3E4r3YFaOBFRNBLZVAqHh+1Av\n7SSeOY2xQz9AC3dQL+4BZKLp1dQnHkGPL0OPzaI48FP02LzghedUiXS+m2jHZdRzz2LV+jHqQezU\n92yEoqNnenFrEyTmXIxTz6G3Bd6tb9VRMz14joVn1VGayTDPqqG2BqBrjR9Fa597/HLswjDhGcGS\nPtQZsBEa+547/r3Zv4dQ5xLS666lvvsZ7Mlh3PIk0blnkVz6TqpbHwgqBHc8jqxEqe59BID4qndh\nTRzFbVRQkm3gOsy48J8QeEhqBN+zCLcuDbzBJihpmfXI8eXg+4Q73k505vtACBI970dvWYsQEE4t\npzb+FKH4bISkYJR3Y9QGKIzciyRrZOd/Dscax/NcRg/fTrxlJZKaQgBWbRAhyRSOPYCsJRDCx2+C\nXqCj0XzB+l6QkIwkUVLdWJNH8GqTCEkQnrGS+Lz1lPc8hBxOYoz3BfS92mTzGTlMOQFT+YQTHN4p\nmwo5OMHY9b0AfIVACJlwYjGWVQcELV3vwheRoNio/XxkJYzve9SLeymPP004MQdFS9E9YyZ3/OLn\nryiQfiqNNE/F0/2vaG950JVlmUgk8qaIiE+3VyvbPZXKt0OHDtE7bxH/z9//A00WOuCdVH5JoCng\nNXVQXQvfdwm1LQHAzB/DKgyQWnEVAKHsAkKdS4Iy0UgKOZoOGk7KCuEZy5v7bgK5Z7/CpBH4TgPf\ndWiUjmJUh5C1NJXJzSSzGyiMPkg8s57y5HOY9QHMxji1yiHCqeW4ToFIZj2SHKEy/Gti2cuwrTLj\nB7+LoqeQtRSN0d+gRmYSaTub8sjduMYwxyey61AdeAHfc0nNvwyrNobeNg/PauDZBkpLJ9WdD4Hv\nk7v7/zD2iy/jmw2c0kQA6pUcWjPB5tZL+K6N1hqAsF0cAkXHPLYL4+jOgLM60U9kzjq0VDdKLEP+\nl/+CFIojKSGi887Ft02s/j0YfVtpW/dpnNIYTmUCJRRHjqSo7XyM0lM/w7dtPKtKtHsNpcOPEsrM\nA78p0O37TUJ/L54xiB6biRbtwco/Tyg+G0mJYRaeJ5peie9ZWPXD2EaOkb3/gusaJDrfiaLGibet\npzByL65dw6wPBUv/8ExqhReJtaxESFrAXPE9nMbkiRXN1HOeAkpJQU1kcSo53NIIQkgokSTxJZfg\nGWXK+x4D38UzKghFI9K5DFmPEW7rRVZDyFoESYs2X9xesF8xfSXnBR41ClOeqhASspJA1VI0Srvx\n3RqeWyM/9BtsYwRJUiiOPYbve6Q7L8P3XSRJx3dquMYod/7ml6TT6ZcJpMNLG2lO71QxNTchWH3+\nLj0I/6vYWx50IfA832gZ8Ml2ctnuyWXBr0VNsyyLj3/84yxfvpKRkdEmBp7ICL/kpdCMzwlZRVJj\nzc8kjIndxGefi5AU1EQH5T334Ls2jeE9NAa2Eus9CyUUxykNE5+3HiUcxxja1fx5s9rola8MmMpY\ny0FipnwY3/fJD/0Wz3XIj9yHpIQxG5Mkui4HzyKUXIGipSkP/ZpE13swa/3UJp/F9z18z0WKzCPS\n+U48p0F99L7gepuKV0JWUcOt+J5DY2gbkhJGCSXxrDJauofG8E4QEkP/+mnyT9yKkHWkios/ngMh\nM/GL/8XQdz6GZ1RR01N83X4k7UTS0pw8iqLHic86l9xd38bJDSJkBS3RAUBqxZWYh7ejxIISUUmS\n0NNzyN/1XYSsEm5fhBxtpXbgGQBCXcsoPHgLSjhDtGsNhX13E+tZj5U7RHz2eViVYWQ1AgjwXWoD\nv8KuDyJHF+GaJez6IJ4IUx55ELsxTr2wi8m+G4PSXK0VRUsSy5yOGunCMnLUClup5TYTis1Di/UC\nPrnBO1HUGEZjMFCTk3UCIJy2Qmo+ZyE3n6nn4NRywXtO1Qn3nIbWvoDyrvuxCsPo7fOR9Rh6uodo\n1zLMyQOEu5ZjFvpRk12BqI/nIsnaiXAX3kuAV0gKUwm1YExLuHY+YLQICTWURlICxoga7kRIoeZ4\n88mP3Ifve+iRDoz6GP/8z199SQXZazXSnOpUMdWR4r777uP888+nWq3ywx/+kBdeeOFl6nzTLZ/P\nc/HFF7NgwQIuueQSisXiy7YZGBjgggsuYOnSpSxbtozvfOc7r7q/39f+IEAXTr1a7NXs1cp2T07C\nvdJxfN/nxhtvZPacXn7+izuRQ90EKk5WU2NEgFCCpbakISnhIC7nu0EizbMCQPY91HiW2tCW45PI\n9zy63vFllHACNdmFVctj5vuRtAjGyF7sah4f0DsXBV0klIDAH5StTj93QeCteMevIRztQdMSqFoL\nkeRCZCVEKLEMRUtiV/cTaz2D8tCviHVcjmWM0yjvRYv2UC9sRQrNIJy9CDO/Cbt2jEjX5QEgjz1y\n4r64DkqkE/CR1QR6ak7AabUaCC1CftOPEZJCqmsDemwWiZ7zyK7+U7R4J5HscmZf+j3iHevB8yg+\n8SM8s46V60eLnshYO7nDaLEsmVXXQL1M4f5bXvJ9fP7bEFoYtQnCAKlVV2KPHkaNB6GM+Oxzj4cY\noovOCzLsp/0p8Z5zMCYPEmlfgucYqNE2XLNEpGs1QlED5oBXBt+hPvYQ1cF/Bzw8YxindhhZz6C3\nvQ1ZSxDJnEmkdT2uXUYJzSR/9CdBUlKJBxKlnW/HKO9DUiIIScexGzhmAVlN4rmNpkcbaCMcB1y1\nKWbj+81nLhHqWkxk7jrq/duoH9mMpMdIrXo35sQhor3n4HsOZu4IcqKL2sBWPMfGmDyMa1XxHRPP\naYKXaIYumiJIMBWGUAE14Ox6BlOCNbKawDYDVkSi9Wx8t4br1EhlL0RIEfAdtFA7tjHKpz71aT7x\niU+c0rycLpCuqiqyLHPeeefx5S9/GUmSePbZZ/nEJz7B5z//+Vfdx/XXX8/FF1/MgQMHuPDCC7n+\n+utfto2qqnzrW99i9+7dbNy4ke9973sv02l4s+wPAnSn2oi8UdCdXqkWjUZfs2x3+nFc1+Wmm25i\n/oLFfPF//COW24rnWjiNYRStBVCapHK5uRxVAg/RNdFiM0HIeFYtSDS1BXFBqziA71p0bPg78Dwk\nLcLwvX+PY1TwLQN74hCJhRuIzFqLUy+RXPVuYgvOwxo7iKLHwHOP984KQslT1+Ef/89z6gghsIxR\nPM9D0dtoVA4SzaynXthMrPVtGNVDSGobkhqjOnY/4dQqapPPYNWH0JKL8RqBbGC4/QKMyadpjD0W\nvEhE6Hi8M5Sci1k6jKy3ICthwm2LaYzvBiEYvvOLuLUCyVkXk5pzKdhF9NTs4HlUBgi19CJJElq8\nE0kK4RUmGbntcxiHX0CKneBRmuMH0TMLg8agi6+icXAzUqT1+Pe+25RlLJ0o/wzPWIFQdEKtgcZD\ncuGlx0MM5pHN4PlUhzYRaVuC7xiYpUHC2eWUDj2K3jIneGZNTx8AKYre9S4QCqHsJait5wM+euu5\n4Pt4TgMlNp/K8D340Ey62SRnXInv2UhKjIm+m5HkENH0meA7+F4D37OxzRxTMdRpoxAh6/iOiUAg\n1BBaqovogrdh5QepHXgCIQTp9R9HDcep7n+EzNkfp3rgcZx6Abs6iTnRhxxKAYJo92okNUw4Mw9Z\nDSNrUWQthpC0pjavzJRmQ9AEMwD/4AWh4ro2jplHUeP4rkV58llcuwa+TXH0AVyrQDS5ANucYOnS\nxXz1q1/53SboSfMvFotx9tlnE4lEuPXWW9m+fTs33HDDq/5mur7Ctddey5133vmybTo6Opp0TojF\nYixevJjh4eE3fJ6vZX8QoAsv5dCeqr1SpdrrxYg8z2Pz5s189KMfo62tg7/54j+QL8mYZo1a6VAQ\nNkDg2lPFD1LTw50Cv+A8reog0dZlIClNGtBOUvPegawnkLUYo499Laiyai6LZ777m0haGCWaCbQW\nDjyOUHTqB5+kdvCpwGsKJ5BUHd9uBNl+NcJUS/aTzfcsXKeOj49ROUisZSX13DPEWs+kMv4AiY63\nUxm9Hzk0E7N6mHr+BZTwDPBsZK0TPb0WY/zhAMAlDccYRVJC4DcCD15SUSNZPLdBdtHHcOwSoXQv\nxb4HAEj3XI6qRQklgxY9jlVFSwZ0Mc8qoSWCGG5jfDeRzFw6z/oH9HA39UMvoKWbQua+j5HrJ9J1\nGgDJ3g0INYwyHZRzh5H1CGZ+AKsQUMXs8lgQIy31B09ICaEns1R3P0R5z6MkezZgjARdOOJdqynu\nu5v47HMwJvaSmHMeZuEIciiFrMWD++vVMEfuR1JieGYOc/wRJDmMVdpBY/xRfATlo7fi2UX0ltNQ\norPRIx34vovVGA1ezEJGi86mMv44emwBQtKYWpm8lNcNCCkQsld0hKYTW3g+Qo9S2/cYvm0SW3Qh\nqeVvJ//cj9C7VqC29DD51A/wHBPPdVDjWZLzLsC36yQXXERjdAfRrjVYpX60RBeiSRULro+AxigH\nYTLfD3RBfM/Gc118z0GSVSRZxXWqzaEmUPQ0spoEBLIasF+6ujq479673nAcdjp7wTAMwuHwiVvy\nGvmcsbGx4wUP2Wz2dQVtjh49yrZt2zjzzDNfc7s3am95EfMpe62b7vs+Tz75JNu2beOJJ5+hf6Cf\nRsOi0aiTSCTBd5k1axaqIrFkyWJc12XGjBnHW58fPXqUsbFJtmzdxujIMLYTVABFk4toFPdimwNM\nxdkUtQXbnMD3JSRZJmDCBFQcIWuBF+MH8dd6fi+yrIMkI6shykcfwbXraJE2XKp0XfhPjDz2JSQt\nyvC9XwxUxcJJaoeeIdy+kFD3Corbf0Ns7lmobfMobvo31FQHSjhObWhP4HnK8rTki0TAvZz6W+Da\nFcCjmt+O79vU8i/iOVVKI/eD79LIb0GJLcKp9iFpadRoD8bEo2iZcxByGDO/CZBQMmfj5Le85L5X\nRp9HSBKh+Bw8u46Z24eR6yM9650kuzeQP/Ib9MQsHKuCaxtosSAEYBsV9GQAunZlgEj7aUiSRPtp\nn6E68knKex4gvvTSJl3KR0+d6CbhOzbVQ0/TsvaDyHoMc2wfaiiNkMNUd/2W9LmfpjH4Imq4hfro\nHpxGCSWcJDxjPYXNv0SPtZPuvZyjA49h13NEuteR23EbkTP+NGBUJHtwjALJ3kup9j/dXGYDvoUk\nJ7GK2wAPJZTBM4JiAD2zHqeyD1nRURPLsPp/giepmIO/Rg13okR6aeSeolHcAciY9cNN50EhKFaY\n7kiIoDLRc4kv3oBnN6jsfgChaKjpmSSXv5PcU7egp2fSsvaD5J/7EUgqofYlGBP7SC1+F7Vjz2BO\n7Cc6cy3Vo08RnbmW2sBmUEIYhWP4rtmM606xGprgL6RmSFlBIIEARUvj2BUQfgDASpRwYin10l6E\n8IllzsSqD5BOCu6/77cvFeb/He21qtEuvvhiRkdHX/abr3zlpV711Kr41axarXL11Vfz7W9/m1gs\n9obP9bXsDwJ0T+4KPMXPLRaLfPYvP8cDDzxIw7SwLROQm4M2kBocHQ30PA8c7MP3HH573wPT4p6i\nGZMNllZ6uB3H8dAjPTh2iUp+Z0CZAaKp5dRL+3DsPLGW06gVd+G5NrISw/NMfN/E9xy0aDd2fQTP\nMYJsevZ0KiPP4poVhKzQtf5vGN9yI5ISZujBvwEhE+teTnVoC9nzPoddHqG09x4yZ32csce+FURq\nXZfi8z8NavD1OEZ+CFyb8JwzAw/owFNMZZt9328mugLwlSQdz3cRSgQ8C8+zkNQUnttAjfUivCqe\nNUK48zKMsfvx40uQQh2YuafB91CSK5D8OlbuKaYvnHzPBqEQSy+iltsOvkvhwL3IikYoOQ+zchQh\nKSihFOXBZ9CirQhJwSoHYQA5lAbAM0toiQBUnfoEkqIRjs1i7J5/JLnmfajhxPHnb5WHkFUdNZSi\nvONOWtZ+GHN4J3pyPrHucxje9FWSZ3wY49gmwi3LkKT9VI8+SWrx5SQXXEph5x2EMqchq1GimUUU\n9t1J68prcMwadnWcSHYxk5u/D75H6fBDJ7xQP+jG4BgTACjxJUjhGTgTj6KlTsf3PVxjDF9LYh37\nMQBqdDZW+QBqdB6N3EYUPYPn1PFcq/mSnCZIE4zuZpm4E3i2vkN5T9ByR2gRWs/9FIXnfkRpyy/I\nnPcZJh//HsbkMfTWBcGL3pgke+5fMv70d0gtuYL6wCbqwy/imnUqR55FUkN4Zg091oVdH0ONZnEb\nuWbyTuDaNWQ1hmtXUNQEjl1GksLY5sRxpbFQvDfgapd2gW/j+xLV3Eai0QRPPLGZzs7ON2O6Ay+n\niz300EOvum02m2V0dJSOjg5GRkZeprs7ZbZtc9VVV/HhD3+Y97znPW/auZ5sfzDhBXipkPkdd9zB\n3N4F3P3Qs7jRWVhGo8kYcII4n+8RbBrIJwZiJlITkETgmUrSNOCVMOpDwZK21h+ED4QgllqOoiWo\nl3bhe3V8z6Za3AF4CEnBdRuEY/ODLLDvY9eHSM28DEkOeqJVhp8lMeM89HgXshZj7Plv45pVwi1z\nAUHXeX+Da1SQQwnKfY9S2PkbPMdi8Nf/Hac8Rri1F3N4F0JWSS17J251Et9qEJ+7Djt3hPrBABwl\nVTuh7QBNSpCE55kIJIQffK5FZuA7NUKplTi1wwgti1Ai2PmnURMrsUs7cBuDSJFZqPFenNIOrPKB\n5hMIgFxWU0F4QU8SSi2lOPgwQlLpmPMnuI5BKD6Lem474WY4oZHbS6gZz62NbUePdx1/gdpGGb0Z\najDLx1D1BNnlf4Hk+kw+cSOSfmLimbk+VD1J64KPUNpzP04tT310P7Guswgle9AiGSp7H6Q+so9k\nz4XEui6gfCDg7Jq5PpAU7FIfALGuczAndiLJGvHOlUxsvZXG5EGsyjiptguQhYKixAJhcKE0y2mb\nvbsq+7AmHgHfwSpswpp8BqHEkLQM4BPpfAeumQd86pNPBnFTJY3X7A7ycsCVQAgis9YQX3AOlX2P\nUTn4DLgOqdVXouhRiptup+2iz4OkMvn4DajxDlJL3old6qdl5fuQwy3kt9xKavlVFHb+CrMwiOdY\nKHqcWNdpyIpGcsY6XDNHtHUprpFDjWYJ4rgKshrDscoIIWObhSY/uxIkhuUQ0eRCjMphLCMPQkYL\nt6JH2pg1q5dt2154UwD3ZE/3tUqAp9sVV1zBbbfdBsBtt932ioDq+z6f+MQnWLJkycuFqN5k+4MA\n3VcSvent7eX9H3g/2ZYI9bFdTaaAghJONhP5gccXtDE3gsywmL4/EXznu3iu2Wz8J6NoKYQARWtH\nUVPUijtx7CpCSGh6FtHM+kpqlClaUaN6gHhmNbISAiQK/b9FUuNo4TYkNYxRPIJVGwcfPNei48y/\nDDwLPc7klh/SmNiHb5uY4/sJt82j65J/RNbjtK77OC1nfAzXqtF+4ecJ9ZyBXZmg7aL/RmTF5TiN\nCi1nvJ9Zf/ITlFgrkhoivuztyLHWgOPb7Cbs+0F8FxTsWj+hxBLM4jZCmbMwiy/io+KYhWDprMRR\n44vwasewq83yVGCKQqRHZuA6NWLps3DtGrYxjlkdobX7vTh2AS2URlJCGOXDaKmgQMKpDaM2Y7tG\n/iChluBvq9xP0CEjmFxW6SiSlkaSJLpO+yL4Alk9IXRj5fcjh7sIJecSis1g8snvIoQglAr2l5h1\nKYUtv0DWomiRLInu8/AdE3NyP9VDjwRdEkrH8ByTSNtKbKOKWepHb12GVewnmTkPSVIJxWYDgmjL\nac1nLJrjY+peeICMCM9GqHGEEkJNrcYzxhBCwhh7ENecQEssDni4no1dPwoo4BnN5GdzMEoyaksX\n0Vmn0ejfijGyF0mW0VtmokQz1PY9Stvbv0hkzhmM3P0lrNIoLSuvxq6MgKyTWf1Bxp/8FqHu1Tj1\nEoXtv0Bv6QVJpmXhu4PO0o6BFu+mkd9HuHUxjWIQSjKrwzhmEdso4Jg5gMAJkRT0cCcat44FAAAg\nAElEQVRCklG0NEIo1CuHEZKKECp6dCaOVft/uTvv8DjKq+3/pm7vKqtVl417k40LxjZgA6aaHggB\nAiSBhM5L6CUQAiGBEEIghVRCDQFC6B0bY2wMNq7gXlRWWrVdaXuZeb4/RhKGAC8Ekrwf57rmWml2\np+zsM/ec5z7n3IfKchcvvvgs4fAHmSNfxPYE3c9TGHHFFVfw0ksvMWrUKF599VWuuOIKAKLRKIcf\nfjgAy5Yt4/777+e1116jubmZ5uZmnn/++S/lvD9qXwl6Ycj2BN2JEyfykx/fhGma9Pf388orr3D/\ng3/j7ZVvDhYklJAUDWEULO/CLFrTb2mQehiq15J1K/dcUQert3qRUCjmY4CJJGlo9ipKhV4K+V48\nob3JJrdTKibwls0l1bcCYZZI9a0BBJoeoFjoxxlqJtnxOsI0MEtZQnsdTbZvE/lkK70bH6aYiqE5\nQxQzcfwjD8JZPZPo6zcR2vvb9K76M8Ioktq5nJ6V9yJJKrEXfmz1ODMKxJ790WBpcIG+5ffTt/Jh\nS6REt5HbtRIjPYCkaTgbppNt34AoZCw5Sbk4WDyxFoBstxWgK2XakBQnsnsUZnoLpfR2rCDPB/mi\nSDKSpFgJ/rKGyzuGZM/rJNqXDNIv4+hp+wcOv5UxYBb70D0LADD2CJyZ2S7USqsdTia2FruvZvhG\nyye2YR/cXlZtSEhkujaSiW3EWTmeTPdmAnVHAFA++nRa3v4huuuDTAZv7Tx6t/wNWbG4OlmWsftG\n0v/+k2Q6N1I38Wq6tv+Rvu1PUTb6eDzhZvo2PkK+fzeiVMDmqicgz6M/9gKByvmk4m+j28sxzRKl\nfHywx9xgRoMoILItgIykaBR6XgdJRXM3UErvRnM1UkzvsqrLrAuIpKmIkmKlgpXygMAWqqPQ14bq\n9OFomkV2x1tIipWvW3X0j0mufZyOxy9HkmV0TwXFdB+lVA9VC66k89VbcI/YDz3YQHz1w2ieMKrd\ni5Hpo3L6uXS982tCk04h8f5j2AIjMApZUrH1iFIWCmkU1QVyCYengUK6Dbu7kWxyGw73SNIDW1AU\nB8V872DsTEF3RACTXHIrc+ftx4MP3I/dbqdYLCLLMrIsf6ECpj2D5P39/Z8ZdIPB4ActsPawSCTC\nM888A8CcOXM+Uynyl2FfCU93yIYSqIfKdnVdx+fzUV9fz5lnnsmrLz/Hu6tXce6538MfCH0g5Dw4\n5RZGfjB4IIaTwsVgkrjFtRWQkFBtASQEmh5Elm0Usm2DN49Bsu8di3oQJZI9S5EVB5q93CqJrNyP\nYr4PMEl2LMFdNhl3xVRkxUa6ez2Zvs0Is0Qx3UNgxCH4Rx0DCBzhqXQsuxVJVml77nKynRuw+Wsx\ns9Z0r3LuRTjCE9FcIRpPeQDPqAVoriANpz9AYPo3kFWdqkU/xL/3yZRyabwTFuJp2Jv09uWY6TiY\nJpLutDz7oSyLISF1UQR7PZqjHGNgPRiFPby6IY0HaTCFKg/IeAITScRetvjo4ExkxYaqhygVOtE9\nlndbzCcpZjrp2fAnivkkvevuJbr0BvLpXkrpGEZ+gHzfVmyDHrAQglx/C64yK1OhlOtDmCUC4YV0\nLf8lxVQXxXQf7nJLsER3V6G7wgjzowLV6mD1n7U+OPJY0tF1aDY/uqMSb+V8MrG3AHBXzSbbswVN\ndROMHESi8xm8ZXPJZWI4fePJZ3txB/fGNFJWzi4GH84UsdL2LDAWSJqPYnI3wixQTG1DGFYXCklz\ngCyjlzXiaJphqc0BimbD0TCD8HE/Jt+9i8y2N7FXjaXmxLtQ7B6if7sIo2TtWxgGjuopVB96I+ld\ny0hueQn/5BMY2PQihb5WAmOPppTuwjfqcCTNQf+Wf1A25Zv0rrsf1e4n3fkuhlFE1ZzYXFW4g+OQ\nZfBWTKWQbsMdaiY7sBVVLyM9sNn6vYWBhEDV/Ti9o8mnd2EUOrj33nt58h9PDHe6NgyDfD5POp0m\nk8mQy+UoFovDxQ6f9x6H/391F+ArArpD/N+Qypgsy/j9/n/qtgswcuRIbrv1p+zetZ1rr7n6w/v5\nJ1Fn+QMQxrQ4XiSKuS7rNd9rFUAg0FS7lRYmTGyeUSiqEzHoCRfzvSBK9HcuxunbC5d/PEiqpffb\nsw6zlCPXvx1fZDahEcdaU2pnBd1r/wQCoq//CGGWCI77GpqzDE/ddML7XYuR7SU09WQ0Xw3ZjrWE\nZp1FNraJ5LbXcTbNIbH+aeKrH8FZP51sbAvxlffhrJ2Cd+LhlEolVIeXutP/QOUR11qBt9oplpaB\nYlUASbpFP5DbSSG1G4SBkDTAzrCHO1T7L2vIsg1FtWMYBrlMG96K+RjFftz+MUiSRDHfD5hE1/4c\nYRqk25aS6d6OhIInuB82tQlRypGNrmL3ixeTi29HtlkBNSPXhxCmld8M5Pp3oNu9hGoOwWavoGPJ\nzWiDpb5ggXQp20sx20e+fzcAxXQMs5TFKAyQjW8CwOautirlbNYU2B1sppRPk40P8dQCl38m7tBs\n8pkYplnC7R9NX+cLeMuaySY3I0k6uqMaWbbxT7eUMAY7OXsQhV4kzQp8odktOU5JxjvxUPzTTqAY\nbyO3ezXIKtUn3k5o3tmk3nuJjkcvR7F7CB9yFcVEO7Fnric491wUd4jk5ldxN8wlcsiNJLctof/9\nZ6haeAPJXSvoW/0Q3pEHASYCQWjCCcRW/JLgpG9QyvXTu9YK6uUG2gjtdTyyJOEMTQZZwSjEsXtH\nkom/h+6uY6D7bUyzRCEXQ5Y0nN6RCFHE5qwFSSadWMsB8+ezft0ajjjiCKvzx6DnqGkadrsdh8OB\nzWZDluWPBeJCofCpQPxRAXOv1/uxn/u/bsr111//ae9/6pv/V6xYLJJIJJAkCZvN9pl0GFRVZd68\neVxxxRXU1tby2pKlFPOZ4XYmH5K1k6x6dAllOAdV1XzWOklGSBJGKY3LNxFVc5JP7UTVA+jOMIVs\nB4HIQSBJlApxZMVJNrUDRIlitgt3+RQ8lbPJJrbgLGumd/tjgCDdsQpFdxJuPpdcfBOBvY7AXjaa\nxLbnKJt6Jl0rf0shGcXMdNO3/jEAktteJbXzTWRFo9TfQaZlFardC4UMqW3LkAAj3Uf/u3+nmIha\ntMf7L5Pa9BoAeqgOs1TCSHYTmvcdXHvtO1hiLAbTzzTrISSsLhaDF8d6ESbOsrnkU1so5nsAk1Dd\n8WR6l+IOzqKQ7yXZ+xa5xFZKxSx2Z5jKkeeRS+/C7ignUHUoxVwMsxQnMvpS3IHp9He9Ri6+BVEY\nwBQmxf4d+OsOsr5rx1LMooG3bAbuwN70tT+Pqvvw1exvjYlMJwPtS3F6x5PpfQd39RyS0Tcx013Y\n3aPJ9r2LJzKHQrqD/tbXMAr9BKoWWAHOUoJk19ukOlciyy4KmZ34wwdRKnSS7t+Ar2I+ic6XCNV+\njXj0efxVC8n1r0NSdISkg5nf49oIrEBYycp0Uay8bIwCvimL0LxhUu+/Qj62GVHKU37AeSiqSs/S\n31uznkQUW7Ce4kAnqruc8nnnke/cSO/yP4FRomz6GSQ2PoHqChKcdgrxdx9iYPPLaE4fCAndVU5o\n0sl0r/4TjvBkVLuP3nUPYZYKSJKKMzQGb3hvEruep2Lc6cR3PIW7cib55G4K2W6MwgClfAJND2Ca\nBRzuOmyOcrKpndhdjeRS2ygL+bjvvnu56MILsNvtw+A4VNoLDIvXDAGqoihomoaqqsNt1U3TpFQq\nDasFGoYxDNySJFEoFIbFpl544QWmTJlCQ0PDv4AY/xG74ZPe+Ep4uqqq4vF4PrUf2adte8YZZ9Cy\nawdz5s4dFHJmuKrqA3CREcJKtRKmQanQPxjBTaPbylE0L+nEWnLp6KD6U55cqgVJVumLvkg2uQ3V\n5ieftXpHBaoXWnXpspPeXU+AMOjb9hiq7qV66qUoupOysd8gn45SzA2QH4jSvvQmkBTaX/kB+b6t\neKqno/tHg2kQmXcF4dkXIckytUf+nODeZyLJMtWH3Uxon3OQJIgc9iNqj70LxeaifO73qD3uDhS7\nD3v5SPzNx1Psj5HvfA9Z1eld8ht6XrkLUciil4/A23wMkmJD9ZThHnMAsisAio6k2Qc5RpN092uD\nl8pucZ1Co5BPkOx7i87tf0CzlVMx6n/QVAd2j6UOZhQ60J2WeE1m4H3snpHW+lIKSVIJjzyXTGwd\nXWt+h6x+EDTLJjbj9FqNKWVVR7eVkU93kU9ZKWeZvvfR7UHKG06iMNBOtmcD2dgqbO6xlNUdR26g\njVz/DlIdb2JzhlFUnYEei1bwlM8l178TUcpR0fRtioUBMv2b8ZTtTza5Fbu7EVlx0Ndhacj2tj5G\nsdBv8bqlBCCQ7J7BYaSDLKM4/LjGLADVjmJzorrLSG54AcVdhlYxEknRkVUbyfVP45/5TYJzvk12\n1yowTSoWXEbVwVczsOEpul69nXyiHUV3IYwCmi9C+IDLia97nPi6xweDvwJ7aCzV+11Lqv0dUtHV\nVM46j96199O/YzGq3Y+q2YnsfQm5xDZK+QS+mn3p2XQ/nshsErtfoJiLgwBV8xKKHGTFKELTQZTI\npVtRFA2b2sODDz7I9m2bWbhw4XDp/FB3liFvNp/Pf8iDHcoyGgLVIWBVVfVDHrGiKMMNA9JpSyUv\nk8lwxx130Nvb+6UKXP0n7SsBukP12V+kFNjtdvPySy+xe/dujj7meIZVuiTZ4jWHOvQOJ6ybSJKC\nZi8nn2nDNKy+WXZ3EzZXI4V8En/FPNyBaYCgvO5EFMWBEAbZ5Hbi0ZdBmKRiy9DtFUQmXmLpw479\nJomWlzFLORLbn6Rv0yNIkkw+vg2ESWTGJXhq52DzRiif9j2Kie34GudgD40kvv5BguOORLF5iK/6\nI4EJR6HYvfS+eTe+UfPRfdV0v3EneqAa94i5ZDvfp5TqoWz/C/GOO4TSQCfBGadQ/80/4xm9AFmz\nE9zndFRXOQNr/oEopDAy/WRa1mBmEiguP+UHXYizaZYlTenwDWqxFikUeul8/0arI2zKmt6XShnS\nfW9TyMfRHA0AFPP92F0Wb2sUe7A5rb9T8VU43PXo9grCe12MrOjkkm0kO1cizBK5ZBRP2TQAS08g\n04HDM5LYhl9bXWbj69Edjciyjjs0m5737iOb2Im/Yj9kWcfpG0t8xxP0ty/FHZqDOzSbeNszgy1p\nykAIVK0CSZbR7FV07vgTXTsfwDTybF99MSUzQzbznkUVyCpIMlqoAffYBai+CKKYQ9LsOBtnUHva\nb/FOPozM5sWQT+EcMZuak+8mNPcs+t99gmLXNsrnX0zNiXeiOny0Pfg9epfeQ2DiIlzVk4g+fjGy\nzUX44KvItq+llE5QfcQvCIxfROfLP0JSNLx7LSCz+y1sgZHUzP8h6eg7JHe/TmTOlQzseIXuVb9H\nVh0gyZSNPQVncDSxtXdRNfVikh1vk0vGKBXT9Le9jiswEWmQQnAFxpKILSFUfTgDvcsxir2Ew2Xc\n9cvbaG3ZyVFHHfUhMShZlofphCGRf7fbPeyhDgHxnlTCngULHwViRVGw2WzDXSWKxSKtra0sX758\nuOvDnoLkH7XPInYzZIZh0NzczJFHHvl5oONzm/S/gNQXl+36D9iQWE2hUCCfz+PxeP73jT7GhnQ9\nJUnizTff/Jh8PnlYeESSdSvIJqx8XFUPoulBMgObGeKAQR6sWLICT5Ks4/KOIpPcijs4GU9oFtEt\nv6Fy1Jn07HwUoziALGvWNM7XaLWxNtLUzb6J9pU34AxPw9d0OLtfvZjK6RdQyg/Qveq3OCNTKCY7\nKWV6UG0eq5WMadEjVlbCoJavwPJKBzVQhRDIqmY1sEz1IkwDX/OxyJqLvrf+TNWRN2CvGEX06esR\nxRyRo35ErmsbsWdvxFE9mWJ/lGJ/1CpHlRWcI2ZZXO3WN/BOPNQC6J1vWfqssgqmYWWLSCrIktUo\nEQmM0nAw0+aeiGb3k0msxu7eC0/ZLEzDpHvnPfirj2Kg83lc5c1k+zbQ2PwTALID2+jc9nvCoy8j\ntu3nuCunkmh9ncio87E5azBNk9b3rkdCon7iDzHNAun+rXTt+D0g4Q7NolgYIJ/cYPHZsqUAh2kM\npheayK4gZm7AopNMA1mzo5U1UujvQCpksVWNIde2DsnuxSxksYXq8I4/hPjbD1HKJcEwcVSPwzv+\nMHqW/ApkGcnmgUIGZ81UUltfI7DPGbjqp9H2yIWYxRzBaSfjG3sY/Wv/SuL95y1th1ATRiaOpGqE\nD/whyS3P0rfuMQQQHH0U8c3/oGzSKdj89USX3owj3EymYzXCNCgfdwoSJXo2P0rV3t8nsf1xCklL\nf8MspdGdEZzeEQx0Lad8xDfo3fUYmi2IYRQpZKLM3ncOZ591Jscdd9y/dH8N2RDNYBjGhxawQHYo\ny2EIiIc+WyqVhr3or33tazz00EP09vbS3t7O/PnzP/ZYl112GWVlZVx22WX85Cc/IR6Pf6zgDcDt\nt9/OqlWrSCaTPPnkk1/oO/JxtfdDNnQBPmH5/8ZyuZxIJpOiq6tL5HK5z7Wk02nR3d0tOjs7RX9/\nv8hmsyKXy4lMJiN+/etff6AUI6sf/I0kACHJukB2CFCEJOtCku1Cs4eFZg8LkIS3fD/hKd9fgCIC\nkcOEzdUgQBI2V4OQZJu1PQhJ1kSodpHQHVXCUz5FNM39pVA0p6iacr6onHS2AEk4K5uFrLqEpDiE\nJKsCSRGqo0x4q2cKWXUKb/0BIjzjIqHavCI04URRf+idQneVi9DEr4nGY/8o7KERwts0T9Qt+qVw\n180WujciKudeInxjjhCSoglv477CUTZCSIpNIElC1l1C0j0CJOEZe5CoOupmofprhLNhpmj4zt9E\n7cm/FpJqF8HZZ4rgPmcIxVMpkGQhqTah+qqE6o8IZE2EF10nIifcKvSKEULS7EJxhaxrqdoFkiIU\nh1+4xx0kFFdISKrN2ofmEKj6HtcbgSQLZE1ImlNIqn2P9YqQNIeQdKdAswtJs/a757aSqlv71hwC\nRbeOL8nWOSuq9Z6sCkl3CMnmFiiaUL2Vwj3uQKF6yoe/l7Nplqg9/fcitP/3Bs9VEVqoUdSedo+o\nPe0eIelOISmaUNxlInLcbaL+2w8L2e4VyIpQ/dWi9tQ/ivozHhC2ytECRRP+KV8TTaf/VVTOv1RI\ng+fuDI8TVQuuFpJqF77xi0TdCb8Rsu4SSIoIz7tcNBz9W2HzVQt7aITwjTpIyKpDSKpd1C64RYRn\n/Y+QFF1UzrxAuCJThSRrwhOZK6qazxeSoouqqeeLsr2OFormFK6ycUKSNSGrThGZdJk1hipmivLG\nY4Ss2IS3fLoAxLx588WyZctEOp3+ty7JZFIkEgnR29srurq6REdHh4hGo8OvTz75pFixYoW45557\nRFVVlRgYGPhfcWH06NGis7NTCCFER0eHGD169Md+rrW1VSxYsEC8+uqr4ogjjvgyIOkTcfUrA7r5\nfF6kUikRi8U+M9hmMhnR29srOjo6RDweHwbbjy7RaFTMnLXPhwFXUj8AXRSBpApF9QrVFhagCUXz\nCpsjLEAefM+6aSRZF+7ARKGobmFz1ojacVcJVfeI8sYTRM34SwSSIgJ1hwvFFhSSrAtVc1uv9qDw\nVEwTkqyLygnfEVVTLxaSrIv6+T8XlVPOEbLmFI2H/laUT/mOUHS3aFr0BxGeeaGQNYdoPOb3oubg\nW4Sk6KJu0Z2i4fh7haI7RXi/y0XT1x8U9lCj8I8+WDSd/KAom/Ftodg8ov6E34nIoTcLSXMIV/0s\nYSsfZZ2/ognFGRT26olCtnuEc8Qc0XjWo6L2G/cISbWLioMuFTUn/lK4Rs4TkqJbIKQ5hOzwCZBF\n+KgbROM5jwnvlEVC0p3CO+FwofqqhoFW9UVE1XE/Fv4ZJwlJ1YVzxD5C9UU+AGJZEb6px4ngnG8J\nSbULxRmw1iu6tYDwTlkkArO+IVRvlZAUTSCrQnb4hK16gkBzCL18hPBOGjquBbiuveaI2jPvFcH9\nzhaSahOSahey3SO8k48Uvr1PsACw+Tgh29xCdviF7C4Tmr9GVB//M+Fs2kcgawLVLmxVE0X9qfcK\n78RF1jrNJfSykaL+pN8JZ+00IWlO4Zt8jJBUXQSbTxayahfe0QeJxtMeEPaKvYSk6MJZNUk0nfyg\nqD7kJiEPPmCclRNExbRvCVm1icj+V4uGo35jPXgkTdQedJsIjjpcKDa3qF94hyifcroFpppblI09\nxQLb5vNF5cRvCVmxicDIo6yHkqSJqgkXCldgjNAdIVEz+Uqh6F7h8DQJTXOISZObxapVq/7tYPtJ\nS39/v4hGoyIWi4ne3l5xxhlniEgkIjRNE7NnzxYXXXSR6Ovr+1Rc8Pv9w3+bpvmh//e0448/Xqxe\nvVosXrz43w66X9niiE8zMShUnsvlhnN5P615ZTAYZMni11izZg2zZs0CBvtSwR7J7aqlsmTkBgVC\nDIqFBGDi9IwFWSeTWIO3fB7F4gBGKY3TO4bo1rsxSlkS0ZcpFa1gQTL2JmYxRajuKEr5PpI9K6mb\nfgNdm/6MMzACT9VM2lfeiL9+P1Sbj8S2RwnudQSYBonNj+IMTyHZtoL4e4+gBxrp3/YyA9tfQvdG\nyHSuJ7lrObLuQvfXkom9Tz7RTuV+l2GaJon1jxJoPgnF5ia+/glUu5+KuRcgDJPdj55FaNopyLqT\n+Lq/YxayZHYuZ/df1mOW8ui+MI6aKWAaZFreIbjvmXhGzSe94016lvwKPVhH51M3IusuzNwA5Qdf\ngrtpH+y7J9H90s8ITP86uehGOp64DklSUD0VBPY+ARSd6N8uxTt+IUZ2gIENz1ui20hUHHIptvBo\noo9egZkbQHH4GVj/HLLmwMynqDjkUuzh0aS2LSO+/H4wDcxSHnvNJIQwSW9Zim/y0QxseJa2+89B\nlAq4Ru1P+bzvkNm5kt5lf8QspHE17UNw+tcJTD2e9ieupNi7C9lbhWzzUHngJbT//UoKvTsoxlso\npXoIzTiFQryFXNtazFwSIclUzr+UvtUP0b/+KZyRyfjHH4mzegodL99EevdbSLJK7cJb6FjyYzpe\nuZHK/S5H94bJxVtRHGV4GvdHmEU63/gZjsoJyIqGpLnoW38flTMuxigkaV/yA1DsKLoHo5jG7muk\nYtypxNbdQ+WUc9Cc5cS3P4uvan8URaVr0z2Ex53PQPQFYpt+hdPpweMyePiZF5g2bdoXvCP/NRu6\nP4vFIk6nE1VVeeaZZ1i/fj1/+tOfmDZtGu+++y6rVq3C6XR+YbGbp59+moqKCpqbm1m8ePG/62t9\nYJ+GyF8G3P+nrFAoiEwmIzo6Oj7Rs81ms6K/v190dnaK7u5ukU6nPzcVkc1mxc9+9rMPT3utOK/l\n1SILWbELkIXurBHe8pkW7SBpQrOFhKTYhCRpwu6qFeqgNxuqOVrYXY1Cs5eJEdPvEA53nfCHZ4sR\n+9wtVN0jKsacLmr2vkEgq8IdnikcwbECSRG6s0womsvytoem05IiVHtAKJpbSLIqHIEmobvDAlkV\ndn+90N1hISm6kDWXRVHImpAUm9AcfqHaPAJJFu7GuSIw9TQhqQ4RXnCVaDr1YeEesb/QA/Wi8ZSH\nRMM37hey5hKV8y4WDSf+SXhHHSwk1S5Ud4WQZE2g6EK2eUTNSXeLxu/8TSjucuGbcKRoOvMRUXfi\nPULSHEIPNghkTchOi2oI7HOGaDzrUVF/+n1CtrmFd+Ii4WzYx6IBFF2owXpRf9ZfReN3HxN6qFHY\nqsYJ96gDLNpAcwoUTdScco9o/O5jovKwq4Wk6EJxBoVscwvPxMOE4qkQjrppovYb9wh/83ECRReS\noovg4HEbvvOIUJxByyu3eUTZ/PNF9Ul3CUm1Cf/k44Ri9wnVUyH8U78mJNUuqo+4Wbib5gpJtQt7\nzRQh6y5Rd+xdwjfuSCEpNuFsmCUk1SaqD71ZOCPNQtbdourQG4TiDApH1RQhaw7hHX2waDrlIRFs\n/rqQFF3YAg2i8fi/iPpFdwvdUyVk3SU0V5moOeBGIWtO4dtroRhx/H3CUTFOIKsiPONiUb/gdqHY\nfMJTO1vULfjp4GzKJhr3u0uU7XWsUDSHqNv3RyLQdLiQZF1o9pAoqz9KyIpNVI07V5Q1HC1kxS4C\n4enC7nCL2267TaRSqf+qdzt0f6ZSKRGNRsUpp5wiTjvttP/Vq/04Gz16tOjo6BBCCBGNRj+WXrjy\nyitFTU2NaGhoEOFwWDidTnHqqad+UUj6RFz9SgTSgOEKl3g8TiAQ+KcnWqlUIpPJIITA6XR+od5K\niUQCWZY55JDDWL36HWCw0kmUQNKRMNHs5RSynYNCKJYEnqL5ySW34AnNQHc10tv6KIHKA5BVN71t\n/8BTNoNSoY/swGZsrgilfGJQmMewgjeqHYenhsxAC87AGNxl0+jd8Te81fvhqzuQ9rdvxFu7AH/D\nwbS9eQ2uqpn4Rywi+tYt6J4wZRPPoGfjA+TjW4nMu4F8fDvRN39C9bzrMAppYit/gatqGpIokIy+\nizAKyKod2eamlInjbtyXwOQTSGx4klzX+9Qc8VMkSWLXo98lMPE4fKMPItO+ltjrP8NWthe57i1W\n4NEsUXPMrej+GmKv/IxiqpvqI27GLKRpf+oqzEIKYRTRgrUYxRyaI0D40GuRJInOF2+hNBADIShl\n48h2H0Y+Td1Jd6LY3GTa1tL14k+RbW6EUcQzfiEDG1/EN/4Q/FOOJdOymu7X7wazhHfC4QSnf51S\nqpe2v12Eu3E2qZ3L0PzVqJ4w+a4t1B5923B5NcLA3TSXin3Pxizl6VnxR9I738QemUjVgssASG59\nje5lv0UL1FF9+I+RZZnUrhV0vX4HeqCJmkN/hBCC+LpH6N/0LIrDT90Rd1BItNDx6k1o/lryfdup\nmPZdEu8/hqTaqJp/Pf3vPUZ88/PYfDVUzbmGYrKN6NKb0X01FAfa8UT2IRldTh0f++oAACAASURB\nVGTOdUhA2xs3Yhp53OXNCCNDMdtFzfQbSOx+ikTrYkyjhN1dSyHTTuXob2OWUnRtewhfZD6p2BJm\nzpjOI4889JlFZL5sE3t4tw6HA1VVWbx4Mddffz1XXXUVRx999L+UInbZZZcRCoW4/PLLueWWW0gk\nEp8YSANYsmQJt912G0899dQX+TrwKYG0r0TK2JB93I+yZ1nwZxUq/yzHcTqdvP76YtavX8/xJ5xk\nAS4A1tOskOsdVN7XcQWmUiomyKe2ozsqSCfW0tf6KLKskOh6nb72p1F1L4XMbnKpnXhC07G7x2Ca\nRSoaTyY88ltIskLd5CvxhRcgIagYdRoAplnCX7+QTO9GSoUM3tr9yfRuIp/pw1N3IMVsL7nETnxN\nh1udjdtX4B99LJIk0bvhfvyNB2Dz1VIYaEFWbZRP/RahqWcjyQqROVdSc8CNKJoHzVVGKd5K6xMX\nkdrxOmYpT9+av9K7+kEkSca71wEA9L77IO6m/YksuIb6Y39lFawEm2h74jJ2PngW6dZ3KNvn21ay\ne7wVIxun5shbqT7iFhTVjZGIUky007/habKxzeSiG6ic/31qjrmd8jnnYKZ7kYw83a/cQTHdR8/i\nu/BPOoa64++mbNa3GFj/NBgFFIcfSZJR7F4wioSmnUJq82u03H8W7f+4Clf9DMr3PZva4+5EVh1k\nW97BEZmIrDnwjpqPs2YqkqSS3vkmye1LkVUb+a4t2MvHkO/aQvsz12CWCiS3L0UP1INRou2Jiyjl\nUqR2vYnqDmPkErS/cJ3F4zkCSLJKKZMguesNdH8dlftdRq7rfRTdj7t6OlXzrkUYRdqeu4S+Tc8S\n3vtCjHyS2Ipbsfnq8O91KPn4bpwV0wiN+TremjlEl/2IYrZvaGSi2gJUTjgXVQ/Q/s4PkVW3pZgn\nyZQ3nkh504nENv0O0zRx+prI9S7j0b89xIsvPvdfA9xSqUQqlcI0TdxuN4VCgUsuuYQ///nPPPvs\nsxxzzDH/ck7uZxG7+aj9u/N/vzKe7lAFSzweHxbCyOVy5PN57Hb7x5YE/6s21CG4VCrhcDjQdZ0X\nX3yRU089jWRyYI9PDir+S+pgLrEDZBfFXAyHZwSByCK6d/4eu6eJsrpT6Nh8K7qjioqGM2h7/2Yc\n3pGU1Z9Ey/obcAWb8UUOom3dTdh9Y3AGJ9C7/WE0VwSbp4GBjjdQbT50Ty2ZnvXIqhObr4lcfLMl\nQVk1nXxiN4VUKxXNZyEkidjbd1F/8M9Q7X5aXrwY/+ij8TbsT8/a+8j3bSGy/w8RRp7dz11A1exL\nsYf2omv178knduGunkEquopiMoqkaNjKRuKoGEt8/WPUHXUnit1L98o/ku/ZQvXCmzGLGdqeu9zS\nPTBK6MEGiqkuvCPnE5xyAgC7HzsP74gDkO1eEhufwMwn0XzVRI74EbKs0v701aiuMgITj6VvzSNk\nomsAifoTf4tic5Hr3kbH8zcQmHQ8iY3/QLZ7MfJpfKMOIjjlBIRRouO1n5LrXI+9chzhA68CWab1\n0fNwlI8h07kexe4jOONUul69jeqDbyTf30rPyt+hOIOUskkajvoFwijSufR2Cv1tCNOk4ei7QZLp\nWn4X2a73EIZB/eF3IEkS0SU3I4w8xUyc8MwLwSwSe+fXBKecTLZtJWY+Synfj81XQ3j2peT6ttG+\n5EY0R5Ca/X+CWUwSfeNGZLuXwkA7gfpDSex+nsDIo/E3HETXuntIxdbgKptCoHYh7WtvwxuZS7Dx\nSHa9eQVmKU9kzDkUM7vobXuB8OjvUMzG6N71GAcccCB/ufcPBIPBL+W++LwmBgsfCoUCdrsdVVV5\n6623uPLKK7nwwgs5+eST/78tgOBTPN2vJOjabDby+Ty6ruNwOD41SPZ5bGgKlM1m0TQNp9MJ8CF1\noq1bt3LuueezfPmy4XWSZEPWnFbfKMDhqqaQ68E0cghRsqgJBJKkIMsKpmkp9kuSZHWRlaRh0RQk\nBUV1YhpWqanDXUsxn6BUSuENTaKQ6yOXasFXOROjmCbVtwFP2SQrN7VvC6rdhzCLlPIDIExkxYYk\ny5hGCVugAdVdTSa6grIpZ+CpmUXXu3+ilGwlMu86TLNEy7PnUTHjfJwV44lveYb+HS9RPvmbpNpX\nkm5fCbKKLdiAd/ShdC//FeG5/4Ojcjz5+C6iL99A3WG3Y+STdK/6I/nebSjOEIGJRyPMEvF1j1N/\nlNWld2DbK/StfdgKCOWT2KunkGl5m7qj70B1BijlkrT+/Xw0b4RisgP/hCNJbluCu24WwSknYRaz\nRF+5iUJ8N6666ZTPuQDMAi2PnkNwwvEkdy+jmIphD48l37ODuiNuRxhFulbeQ6b9XRzhSVTtZzU7\nLCRaaXvucmSbl5rDb0O1uSlleml56iJAITzvEpzhCZRy/bQ+eQECiao5l+CsnIBRzLD7yXORZIXa\nhbej6m4ysfV0vvULJEmi/qA7MUsZ2t+4Ed1bRTHVhc3TQDHdjqzaCe9zNfm+LURX/BTNFaZ+9o1k\n+zYTXXMn/oaFDLS+hqw4EEaW6qlXYRbTtK+5zeowbRawOasoZDupHncZ2YH36N75N3Sbje9fchFX\nXHH5fw3UDMMgk8kgyzIOh4NCocBNN93Eli1b+M1vfkN1dfV/5by+RPvEC/uV0F4AC/iGnppCCNxu\n95fm3QohKBaLpFIpgOGqmz2zJYY440AgwBlnnM73vvc9fD4/q1atIZ9PI4wcsmJDmAWEmccwsqia\nj4qG0zCK/QgjS2XTt1A0H7n0diobT8Ppn0Smfz3hEd8iFFlEsnc5VSO+Q3nt8fR3Laai6VSCtUfT\n3/kSZQ3HEKw7ikTHS/iq5hJqPIGB2Js4vDVUjDubYjZOMdtB3T434SprZqB9CXWzbsBXu4Bkx5u4\nK6dhc1WT7lyFUcyQjr5D/7YXKCR2ItsDSJqD5O4liGKK4PiTkCSJ7rfvJjj2eNzVM1BsPlKtywjP\nOB8jN0B8/SNIsoJRSKH76+le8StckWl4ameh2n30bXiMwOhFOMpGE9/wOJn2d7FXjMFVv6/F5S6+\nleDEr1Ex/Sx0b4TEe09a1WHucmyhJmKLb0d1lVF9wDXY/HX0rXkYM5/GP/5oNE8FwjDoW/swZZNO\nItOxjsT6x0m3rUK1+Sibdgbepv0swfkdr6MHGvGO2A9J0Sj2Ryn07aSU6qCUjeOKNBN/7ymMXD82\nfyN9ax7AXjmRvjX3I6suAiMPpfud36HYvPRvegZZsRPc63C6Vv0e1V1BNrqaUqoTR3AUifcfxVUz\nG4RBsmUpQoAsq7gqJ+OOzKB3w8MIo0jt7B/grpxBf+trpKMrGGhbhtM/mlKuh1x8M4HGw9DsIXq2\nPIJqC1I37TqMfA+92x/BHZ5NPrmdQrYbh7uJ8KhzKBV66N71VzTdgyon+NXdd3L22Wf9VwB3yLvN\n5XLDM9B169bxzW9+kwMPPJBbb731M0s2/h+3T9Re+MqkjOVyOTKZDIqiDE9Vvgz7uABcOp0mm80O\nV88MlTMOpbcAhEIhLr30+1x44QW89NJL3H//wzz/wvMUTAnDyOHyjaeQixLb8QcEoCg6Pbvvp1hI\noepe+nveIZ/ajG6vpFiI09v2ODZHFYrmpmPbPWj2Mly+8fS2PoWk2PBUzCbZ8y7FXAJf5ECKuT6y\n/Vup3ftaS1M4+jKhkScgSTI9m+/DUzkV3RUm1fUuplGgbPRJIGkMtL9O5YQzcZU30/Xen8n3b8du\nD9G79n7MUhZFtRNbeSeyzY9hlHDXzAKgb8N9+JoOwFkxEXvZWFLtKwjutYhs31banr0cJHBF9rZ4\n5ZZlCKOAf+RCS9O4lKN/+0sUE220PH42mr8OAXgb5g4KoRRBkghNOIm+1Q/Rt+7vmLkEtQt/jCRJ\nOMKTAQlHxXhir9+GIzwJgcDmq8M38mC8TQvoXvsAyZ2LcYQnWpV4sky2axO6v4HSQJTWpy+hcv8r\nSGx6msrp56A6gnQsu5XW2HsUkzFqDrge3VtLfNMTdLxyA0II6g+5A1V3ozrLiL19N0IY1C/8Baru\nRtY9dL39O4RpUL3vNdi8dfSs/wPtr16NKcl4q+fiDk+nY9XPEcJAtbmRFR1JsRN951bCUy8hsvdl\n7FpyKZKsUTn+u5iFftpW30LH6p9TzPVgc1VTzMbo3f0PQk0ngyTTvvoWVM1D/YQr6dj6G9o33kzV\n6AvJDmxGZztL3lhCKBRiYGAARVE+tHxZM8JPsiEVQLDK7g3D4JZbbmHFihU88MADNDU1/VuP/3/F\nvjL0gmEYFItF0uk0mqZhs9m+0P5M0ySbzVIoFIZ5WyEEpmkO15DncjkMw0CW5eH1qqp+aCDv6U0k\nEgn++te/8tripbzy8ktkMmlkRccfPphscju55Fa85bMRQpDsWW4FsHQPuUwUhEBWHRil7ODexKDi\nmW4F8YSMJFvHszqz5pEkFd3hxyhmKeYTuMOzUHQf/a0vE5l6Mc7AaFpXXIMnvA/+xsNJ7H6ZRMsL\n1M/5CUJAy9JLKBt7Ku6KqfTteIZkdCnBkceR69vAQMfbIEnYPGG04BiSu16h/iCLH+7Z8BC57g1U\nz/0hkiTRsuQHKKqdYrYbYeQRpklg9JEExizCNE12P3seZRO/gbt6JumO1XStvgdJUvCPXURgzBHs\nevoCfCMOJrDXYZilPC0vX4GRS2AvH0vV7AtJbH2O5I4l1B18G8V0F7G3f0UhGSU06UT8IxcC0Pry\ntag2P4WBNpAkyqZ+k9ibv6B2wc0oNh9dq39HunMNmruSugU3W2OqkGL3C/8DpqDmwJvQXRWYRoHd\nz1+EWcziH3UEobHHYhaztLz0fUyjgDsyjYqp30WYJVpeuZxSNo5/xBGERh+NECZtS6+jmIpRO/t6\ndHcVucR2ou/cjmkWqJp8ETZ3NdHVP0G1+9FdEdJda5BUJ7IkEZl2NaVcHy1vXYuk6DROv5ViNkr7\nxl/gDIynmIliFvOUSkkCkYUEwvvTufUesqldHH/8cfzm13dhs9mGx/FHy3AlSUJRlA+N4S9rpjhU\nom+z2dB1nU2bNnHxxRdzzDHHcMEFFwz3Nfy8duaZZ/LMM89QUVHB+vXrAUtv4cQTT2T37t00NDTw\nyCOP/DeChF99egEsoCwWi8Pg96/YEG+bTqdRVRWXy4WiKMPSdACFQoFcLoemabhcLmw2GzabbZhy\nGDqPoRSYoW3tdjt77703Jxx/HP/zPxcze/Y+jBo1knjPJlp3rUVRVVwuN6nEFpBkKhpOQ5Id5FLb\nqBp1Hr7K+aR7V1BWcyRVI79DdmA9Tk8T1aMuplRMYBppqkedj6IFySbfp6Lx6+iOWlLxdXhCzSjC\nYCC2AlmWGYguo2/H05ilAka2i1T3GtKdK3FXzcIRHE9i9wsUUq2UjzkFSZLo2nAPwZHH4qmaiWma\nZHrWUz3tUiRJpX/niyAE+a61lAopkrtfIzTuZHRPFYVUjMS2J6medQWBkYswixly8a3kejeT6dpA\nMdlBMdlGRfO3kCSZdOcaCgMtlI8/hfimf9C78e9gFgnPOA9JViikYgxse57IrEvJ9rxPz7oHyHVv\nobz5DGzeahTdTbJtOYqik25fSS6+E0X3MrD9RSL7XIZ/xCEUk+30bXwUe9ko/CMWIskquqea5K7F\nmIUMplnAWT6OTGwdmY7VuKtm0Lv+PnR/A5m25RipGFVTL6Bn44MUk23k+7YgCikie19GfOs/yHav\np5iOURpoJTz5Ano3PUApFwcg2bYUX2Q2PZsfwhEag+aqYqD9dYRRQpYlPOGZuCtnEN/1LJn4Vqon\nX0kgMp907yoSrS+ST263ZJc0L8nOV/FVHYQrMI6enY9iGgVqx1+DyzeG3tZHyfS/B0YfZ5x+Kr+6\n+5fD98SQMM2QvKKu6586fj8qsfh5gNg0TTKZjJUt4XQiyzJ33XUXd999N7/97W858sgjv5CHHQwG\nOfPMM/n73//OOeecA8APfvADJk6cyMMPP0w0GuXll1/mwAMP/JeP8S/aJ9ILXxlPd2igDAnWOByO\nz7X9EG87RFE4HI7hAThkpVKJXC43TGH8b09n8TGiHkPdivf0KIa44V27drFmzRoeeOAhcvkS27Zt\nIxpts0TZg/UM9McwSiUCkUPIp9tJx1dTM/ZSANre/ymRUefjcDeye8MP8JbvQyByKLHt91HItVMz\n/grymXbaNt5K/eTrUG0hWtZeh9M3EZurloGuN8il25BlDaOUs5oR2jx4wjMRSKSiS6mf81MkWaF1\n+TV4qvbFX38ohWwPrcuvJdJ8MfmBnfTtehZhFLB5a/A2HUqq5VU0RxllE860znPplXiq5+Esm0Ri\n17MkO1Yh27yEp5+PPdDAzufOo2zsSXhqZiPMErteugjTyKE6y6mccS7d7/4Bm6eOislnIISg8507\nycTWoLnChGd/H4wibYuvo3a/mxDCILbqbgqpGO7qWVQ2fwuAVMcqut69BwBHxQQqp59H22vX4vA1\nWWlYq36BzVdHPtlOoOFgAo2HMtC6mO5Nf7XogplX4PA3UUjHiL59K6X8ALWzr8fmjlDK9xN9+ycU\nsn1Epl6C0z+SfKqd6KqfYpRylI04Hn/tAhKtz9O381l0TwTJKFE+6kza1/0Mh78RX90hRN+9A91e\nhhB5IpMuR1bs7H7nGoxihpoxF2Jz19K98y+kEpuQZA3dVoaiOMimdlBedyJmKUVP29/59a/v5pRT\nTvlc98Ke4/fjPOIhwP6kGd2e91Mulxv2bnfu3MkFF1zA/Pnzufzyy79w6uaQ7dq1iyOPPHLY0x0z\nZgxLliwZ7gK8//77s2nTpi/lWJ/DPvHJ9JXhdD+uOeVntY/ytqqqDsvLDQFvNpv9J972s5zTkEjz\nkO05iIfk7cBSV4pEItTV1X0oL7FUKhGNRtm1axeLFy9GCEFrawcrV/aRsYXp2/1LUql+JFkhH3+a\nZKxEIdeLEDL93StI9q2maq9vA9C9814C4blo9jL6Y8sxillCdUeDpNLb+gQVI07CW7EPPbueINn9\nFr7ymeTim8kMtCBJCtG3b0Z2VFLI9OGt3h+Ank1/wVM5FYd/L2zeESRansdXdxQYGXrW3YtpFnEG\nNUq5BPmBFoq5frw1+yOrdnRvI3L3Rrzlk4m+cROK7kKSJNyRmQCkOt4GBA3zbiW+81naX7seMKmc\n/B3AaoOT691MePJ3SfdspO3Vq0C24Y7MQnOWA+AfcTjd6/5IOvoWPbqLsvEn0bvhfkIjj8ZVMYWO\nd++k5YWLMQppaqZ/H0X3ULfvD2lZdj3CLOCpss7FU7MfA+3LyPXvYqDlFRz+JjRHCFnRkRUbsTV3\nEplxDYrmsjp/yDa6N95D9bSr0V0R7N560vGtpLvfxlu9H/7aQ8gn20h2v0uobhG6M0xt81W0r7uN\n9tW3E4gcRKj6ULp33kfb6htwBCciCZNg5Tyim+8iWHsk3or5JPs2IIwCqmck5XXfIB1fRefOv+D1\neFi6dAlTpkz5XPfCR8fvEKgO2UeBeMgT3hOIhwTHAVwu6zf9wx/+wMMPP8zdd99Nc3Pzv3xOn8Vi\nsRiVlZWA1X49Fov9W4/3ee0rA7pD9lHv9NNsaOozVAUzxNsO8VsA2WyWUqmE3W4fnn59ERtq0Df0\nlB8qDRxKeduTJx4axNXV1dTW1jJv3ryP3Wc6nSYWi9HZ2cnGjRtpaWlhYCDNho3vYSZDJNrup3tn\ngWIhh9MZIN72JInYMrwV+wDQ1/Y0smLDUz4T0yyR7FpGWdPX8ZRNJd5uJ5/ppmrU2WQHttDb9hzC\nLNG64loUZ4RcfCt1M68DoL/lRSRJw197IJIkkx3YhTBLyEDLksuRkHBVTh1uqdO/8zmCTUfhq56H\nr+4wWpZfjWkW6Vh+E6FJ3yKx9XFCIxah6l7KR59ELv4+pXyS9mU/wtd4MEa+H91Zjqtyb9zh6di9\n9XS//yD5vvfJJ9uxeapJbH6Usr2Ow+ZtonP9r0m1L0eYJr66A5BkjZpZP2DXkkuQZJlMz0Y8kVlW\n/zUjh6d8Ci1vXEflpLMQokQx3Unt1Kvo3Pgr2pffiLNiCsLIUz/rp/Ru+RNty67BVTkVUcpRP+PH\n9O64n9a3rsNbPZfcwG4amn9AbMvvaXv7OspGnkyqew3ByCHEW5+mmO2kbMQJVtqgYifV/Sae4FTK\nm04nu/YGUl2r8IRmEKo5FrtnDB3bf48wDYLhBTgDk+lpeYiWDdfh8tYzcuQoHnzgXsaPH/+FxurH\n2acBcalUGgZhgBtvvJHu7m62b9/OhAkTePbZZ//j3OrnpUP+E/aVAd3P4+kO8bZDUx+fzzcMtkM2\nlH6maRoej+ff9sMNDYo9u17s6U0MtS/Zk5bYM9osSRIul4umpiaampqYPXv2P33XYrFILBZj69at\n9PT0sHXrNp54Iko6s5uWdy/FMMDhCZOIvkwu2YKieXCHmi0BnPYXCdUfj93TSDHfhyTJNEy7mVy6\nha5tf+H/tXfm4VEVVv//3Fkzk0z2fSELBEIgrFnQX9FiCRVFfFGrgta9tb5aRagKLy+LWgSLYjWt\n1YfaV6zVqijiCghVcSEkBAlohLCGZLIvk2UymfX+/hjuOAkDYcnO/TwPf8wMmXtmO/fcs3wPohNj\n0Wq0AXFY24yEDb8RQVBg72jAYjpEwuSlaPRRtFTtpO7wvzDXFlP25R9Q+cfjdNoJjHHb21qdj0Ll\nx7CJj9Nc8SkVO5YDIn5hYwGwNB/FZq4lccpTWNvKqT3wGk57G+Ejr/9pb5bxC0ISfo4gqDB+8wRq\nwzAcDhuBcZcjKNQk5Kzg+NePIgCtlfkExk/FdHwLCoWa0OG/ovaH12iv34+1+RghCdMJTZ6DX9VX\nVH33IoIAoUnXojUMI37yMir3PUfD4Y+IHDkPpUpDxOjfUlPyMi3GnQTHudf+hI+4A5fr/zCVbccQ\neSlqvzBixy6g5uA6Kve/SEDIeMLiZ2IIm0BFyfO01RWh9gshedxKTNWfUPHDM6h1UTidFiKT5tJQ\n8T7lJUcwhLlPvlr/eJpqv8BmrSc88ddUH8ojMV7L9m1bPD3kfYH0HXY4HJ52TYCUlBSOHz9OQkIC\nP/zwA7GxsXz++efk5OT0qj1SWiE6OpqqqioiIyN79XjnypBxuhJninSlKqrU7iU5U29nK7W1KJVK\nTxGtr/GOJiRn7J0flnJlwBnbfrxbdGJiYkhISPA8tmTJ/wBuzYri4mJKS0spKCzik0++o7alkYbS\np7HZFbhEJzqDu5Wnsfw9wobNQqUJQm0PxeWykjhhGU57G3XH/o3Tbqbh8Fu01ezEYTdjiJiARu++\nzGuu+ITQhJkEx+XSWldE3ZE33QW6H9cTOuJmWsq3Epp8HSq/EMJORoEKdRAV+U+gD0vDYWkgJGEa\nKm0QKm0Q+pBULKYjNBzaiKV+PwFxU7GZ64jJWIhS7Y8udCKV+55DodRiNVfhZxhGw+F30eoiCI6f\nSe2Bf9JWvYuO5uNEjrqDgPAJ+BmSMRavxWk3ExDpboULjJlKs/ELrG0VtDcUERR7OYLSD5fNhF9A\nAvWH3wIEAiImYmk6gCE8E5PxPzhtTYSm3Eh74w8YwjJpq8tHdLYSMeI2rOYT6AISMZv2U3d8A+GJ\n16PWBmFrr8Nha6atcQ+hsddgaTtBe8sB1H5hqLQRJIxZQtWhv1Jv3IRSZSA84VeIooO6stcx/riG\npUuX8Oijj/R5ZGe327FYLGg0GvR6PXV1dSxYsID4+Hg2bNjgOQFI9ZDeZvbs2axfv57HHnuM9evX\n+1hG0L8MmUIauLsKpLaxrg3W3nlbSVBD6iromreVHh/oeOfWpPSE5LAlJ+3n5+dZlXK22O129u/f\nz7vvvsuugu/4/vt9OJwiFnMzUSNuQx88huoDeegMwwlLvBGXw8bxvYuJTLkNpSoAU/VntDX9gEql\nwy94NFpDMk0nPiQpaxUKpR+N5Z/SWr2DyJRfY6raitl0CASBYZnL0fhH0VS+jebyzSRmPoW9o47a\nQ69iNVfhH55BZNqduBwWTuxaQmzGQpQqAw3H3sTceABtYBLxE92FxdrSN7CaDhIQNp5G438IiJxI\nW+13xGbMRxeYgsPaRPl3q3A5rUSPuRf/0DG4HB2U7VqE1j+BjrYyQlNuQKnSUVf6OvFjH6Wh7G2s\n5grU/vG4bC0kZCzG3LSfmiPrQVChC0gkZtT92DuqqTz4Ig5bK3rDcGJS78duraP68EvYrE1odTHE\npy3A2l5B1ZF1uJxWBIWWhPRHaW8uob58AwqFFoejg5gRv6Gj9XtMtd+gVAXgsLUSnjAHm+UYrQ3F\nqLWB+GlFXvrbX7j22mt766vmE5fL5UmH6XQ6lEolH3zwAWvXrmX16tVcccUVvX4CmDt3Ll9++SX1\n9fVERUXxxBNPcO2113LjjTdy4sSJAdkyNuScrsPhoLW11fMme+dtpeEG735bKdUgrQI5Vwc1kHC5\nXJ5+SO8trAqFolPvpZSWOFtEUWTv3r18/PHH7MwvYufOr7F2WAiJuRz/0CxM1dtw2VuITXsYQRAo\n3/9HdIEj0RnSaan/GrPpIAqVH0Gx0wiKuYITRf9DZPKtBIRNwOWycaxoEX76BCxtx9AGxGFrryUi\n5SYMke7L0BNFS9AZRmGzVGKz1IJSi96QRFSaezdWU8VnmCo2IyjUKBRKQlJuoO7gq8SmP4AucATW\ntnIqvn8ORJGo9N/iH5JOR+sJjPueISRmGk1Vn7udrrMDQRSJGfV7zE37qD68HnAQkXQDQVGXI4ou\nao/+i9a6QvTBo4lO/S0KhYK64+9iqt6OWhNEVOo96AzDqTn6T1rrdyMICoKjcwmLnUn10f+jrWk/\nIBIQMoHIxHnUHn+dNtM+QERvGEl40jzqT7xFu+lHQESrjyUo+iqaqz/BaqkB0YVKrUPtF4tSaCc8\nVMumTe8yfPjwnv0ydYMU3Ur70EwmE4888gh+fn4899xzQ2Wq7EIY+t0LRBfsNgAAGx9JREFU8FNu\nSSpOdZe3lRxUb+dt+wKpnQ3c0z7SZZx3WsLhcGC1Wj354a6O+HQIgsDEiRM9VWe73c7WrVv56qtv\n+ODDjZgbj2MIHYm5qRi7rQm7rZnY2GtQKnWYm0tQawMJivg5LbVf01j2IYJCjVLtzvvVHl6Pnz6G\n2LQHcdhMVB78Cy6HBZPxU1BocHTU4XLYCU+6CUFQ0WTcSkPFh7S7Smks30xQ7DRMFZ8SmXIL+uCx\nNFd/Tu2P//DsrQOwW5sQRSehMblUl7yEPigFu6We0JifExo/G0P4FKpKX8be0UBYoltCMCB0PLqA\neDraymk48QEiCgLDcmhv2kdQxKW0t/zIieKlhMReTXPtV8Sm3oe1/QTGH/PQ6GKxmiuIT1+I02ai\ntuxNWmq/xOGwEj96IaLLRkP5vzm691FEl4PYtIUIgoCp8gPK9i0H0Ulo7Cx0QWMxVX9M7dFX3Isv\nNYGodQk4bXVYzUf43X33snrVql6fJPNGFEVPcVmv16NUKtm+fTtPPvkky5YtY9asWYP6d9QXDKlI\n126343A4PHq30krnrnleqUtAoVCcVb/tQEbSnLDb7WfdYeGr9xJ+yg979w+fDaWlpWzbto13Nmyi\nsDAfP10Ehogr0OjjqDzwZ2JT78cvIJkOcznG0j9jCJ1Aa2MxSpUfDlsb8ekPozOkYLPUcOL71USn\n3I3dUk5D1TZE0Yl/6Hiih98BQHnxMgzhl6DWRtJQsRGHox2Vyp/EiX9EEARaG/ZQc+SfGELG0Nr0\nPf4hY7G0HCI09kqCI3+O3dqI8eDzOOwtBEZcSviw68HloGzfUvwCUmlvLkHrH4UueAKmyq0MS1+C\npe0IdSfeAlFEo4shbtRDgEhT1cc0VX+JUuVPfNoCVJpgmuvzqT/xNoJChSHsEkLjrsZU8zmmqq0A\naHXhBEVfjdm0m/bmUlRqfxz2VjS6OBy2egSFFr1hOK2NxYii3T14CKg1ITidbbgc7WSMm8i7G97q\nc1EYKUWnUqnQ6XS0tbWxZMkSzGYzeXl5hIeH96k9A5yLI71gsVhobW3F6XQSEBBwxryt5KAGK96j\nldIl3vlGGF3b1nw1watUqrNKS9TV1bF9+3beevs9tm/bgqDQEBx9JfrADKoOv0BgWDbBMTNxOq2U\nf/8EgqDC6WzHTx+D3dZCQHAG4QluqcfK0udxOq24nO24XFYUqkBcjg6SM5YjKFS0mfZTffQfKJQ6\nFAIYIi+nuXo7YXGzCQy/FGu7EeOhvyC67ASETiYy8UZslioqDvyZ0NiraK3/FpfLgqDQodEEEz3i\nfre494k3aW8uRe0XSezI+1Gp/Kkt+zetjbtBFNEFJBI2bC41R15CpQ1DqdTSZirBzz8ZS9txwuJn\nolKH01T1MQ5rIy6XnfCEG9AHjaGl7ktMNTvcU3DaCALCcrBaqjA3FoKgQHTZUar8cDrtIDpxb5V2\nExoWzicff0RGRsZ5fc7niy+B8W+++Yb//d//ZcGCBdx0001ydHsqF4fTbW1tRRRFzGazZw27lG6Q\nosHBnrcFd8RhsVg8k3e9Eal79176mqaTHPGZ+iBbWlrYsWMHGza8z0cffYDFYiYs7pfoAsfTVPUJ\nDlsjsSdHmKuP/B17Rw1KlT9+ASmoNZG0NHxLQvpiFCp/TNXbaKr+DEEQ8PNPICRqJjXHXyU0diaG\n8Etoa/zOHY2iwBA6mfC4/6LV9B0N5e8RPuxGWut30NFeDbgIjrqM0NhrEEUXVYdewtJaikoTSGDY\nVIIiplJ+YCU6Qxqisw1zyxHU2nBsllpiRz2EQqmluXozrU37AIgYdhMBoZNord9FQ8VGRFyo1MEo\nNWHYO6pxOVpw//7O/6c0depU1q9f72n470uk75o0pdnR0cETTzxBWVkZf/vb34iJielzmwYJF4fT\nlQppZrMZh8PhicycTqdHBGewpxKkol9PDWucC13zw13TEmfKD9tsNnbu3Mn773/Ie+9tpL6+hqCw\n8eiCs7Fb62is/ITY1PtxOsyYajZjba9CodCgC0zDEP7/qD26juCYXHQBo2mt/4rm+l0IghJDaCYh\nMVdiqt5CW9NeQuP/i7aGb7C0VYDoJDj6F4TGXoXL5cL440qcTiuiy4afPg6NPoWW+q+JHv4b7NYG\nTNVbcdpbQVAQk/rfaPXxNFRsoqXOrY2s0hhQKAOxd1Qhiq6TvtSJoFAjIoDLhnBy8APRieh04Psn\nJDlhBe5I9ienrFarmTlzJsuWLSMpKemcRm97kq7RrVqtpqioiEceeYTf/va33HHHHT2WS05KSiIw\nMNCjBVFQUNAjz9vPXBxO96677qKqqopJkyYREBDA/v37WbVqFXq93iO/2FUFrC+LEOdLT6YSehpf\nbWvdOQiXy0VhYSFbt37GRx9v4Ycf9uGnC0UfnA0KPU3G9wmNvQqFykBrw9d0mI2AAp1hOAFhl9JS\nuwXRaScw4nJ3brTlKAhK9IFphMVfi8PeRs2Rv6HVD8PafsLtFEUXSoUfsaMW4HS0Unv8dewdNQgK\nDX76eHTBE2iq/MS93sbZhtNpQVCoEE+KxXeP23EKSg0q/0jsLRUISu3Jv1cBDkAJ/FTIHT16NHPm\nzOHWW28lMTHxtM/cnYbH+XalnA4pupUExh0OB08//TR79uzh5ZdfJikp6YKP4U1ycjJFRUX9tsGi\nl7g4nK4oinz77bf8/ve/p6Kigssuuwyj0UhqaipZWVlMmTLF01rjy0Gcbd6yL+mLVEJP0nU23+Fw\ndGpbA3fUKxVjFAoFDQ0NfP3112ze8hnvv7+J1tZmwiPTsTmDaW0sRB+Yij54Iq3139LRVgaC4K7k\n+w3DYW/AZqkmKOrn2MyHaW856t5NJ6gwRFyKRhdHw4m33RKYrg53fh8FLpcFtV80KnUwHebjiK6O\n07wi79SAAAo1uGwnb6pBtPv4ExWc3JkXGhrKr371K+666y7S09N7dItJd464u/SPr+f0Xp+jVqsp\nKSnh4Ycf5qabbuL+++/vlSAlOTmZ3bt3ExYW1uPP3Y9cHE4XYMuWLRw8eJD77rsPtVqN0+nk4MGD\n7Ny5k/z8fEpKStBqtUyaNImsrCyys7MJDg4+owpYf0TD/Z1K6EmkIl1HR0en/ujTta3V1NRQUFDA\nO++8y57v9lFXW43D4aTD2o6AAj/DSDrajvpwlCcv1wUliCLeRaifLuXPgHDyhCZK0ahXZCqokDSM\nJQwGA+Hh4aSkpHD99ddzyy239OtQTXddKWe6uuu6PsflcpGXl8e2bdt46aWXGDVqVK/ZnZKSQlBQ\nEEqlknvvvZff/OY3vXasPuTicbrdIYoibW1t7N69m507d7Jr1y5qamoYNmwYmZmZ5OTkMGbMGM9G\nCO8vbk+LO5/OPimVIOmcDlZnC6d/PWdyEF3fZ1EUqaqq4ttvv8VsNnPs2HFeXb8ei8VCSsooDh7Y\nj9V6ukjVB4LS4zyltkIAnU5HXFwcs2fPJjg4GEEQuPbaazsVsHwJcg/kz+dsHLEkVCOd3A8fPsz8\n+fP55S9/yR/+8IdeP5FUVVURExNDXV0dubm55OXlMXXq1F49Zh8gO90z4XK5KCsr80TDxcXFiKLI\nuHHjyMzMZMqUKURFRXX6Al/olJcvvHNpg71/GM7t9ZyNdmt/p38kLQsp1TMY6gFd6SqmZLe70yNf\nf/01//73v9Hr9RQXF7Nu3bpeF6bxxeOPP05AQAALFy7s82P3MLLTPRek3NZ3331Hfn4++fn5lJWV\nER4eTlZWFjk5OUyYMAGNRuNpqwJ85tPOBu9UgtQHOZCjp+7wrnxfSGqkJ9rWegJfuc7B/vl4R+tq\ntZq9e/fy7LPPUl9fj8VioaSkhPvuu49nn322V21pb2/H6XRiMBgwm83MmDGD5cuXM2PGjF49bh8g\nO90LRRRFampqPE549+7dWCwW0tLSPGmJ5OTkTkMG3UVpQzGVICmg9VaXhVRA8nbEcHZ5y/OhayV/\nMEa33khaJIBnO8q//vUvXn31Vf785z97olur1Upzc3OvyyIeO3aMOXPmAO73+pZbbmHx4sW9esw+\nQna6vYHD4eCHH37wpCVKS0vx9/dn8uTJZGdnk5mZicFg8BmlgXts+WxX/wx0pNFql8vV5ypt59O2\n1h2++lQHM77W59TU1PDwww+TkpLCU089dc4rrmTOiOx0+wJRFGlubqagoMBTpGtsbCQ5OdnTshYS\nEkJJSYlHbLy7DcIDHe9L74FSWDpd29rZ9rVKClpSkW0oRLfesqUKhYKNGzfywgsv8Kc//YnLL7+8\n3z+zIYjsdPsLl8vFkSNH+PLLL1m3bh379u1j2rRpjBw50pOWCA8P7+QkeqvpvacZTJfeXftapS0H\nXQV+pKnGoRbdSumrpqYmFi5cSFBQEM888wyBgYH9beZQRXa6/c3TTz9Nfn4+a9euJTIykqKiIvLz\n8ykoKMBoNBIdHe3pGx43bhwqleq0Ocv+LrQNlcJf1wWLkhKdtEx0MF55SEjRrffq8y1btrBq1Soe\nf/xxZs6cOShf1yBiaDrdd955hxUrVnDgwAEKCwuZNGmS57FVq1bxj3/8A6VSyQsvvNDv1VApgvWF\nKIpUVFR4inR79uzBZrMxduxYT8tafHz8KS1rXQc4evtH1BeFsr7G2zlJqYTTta315Xt9IXivz9Fq\ntbS2trJ48WLsdjsvvPDCUBu3HagMTad74MABFAoF9957L88++6zH6ZaUlDBv3jwKCwsxGo1Mnz6d\n0tLSAX352xWbzca+ffs8jvjIkSMEBwczefJkcnJymDx5Mjqd7pQi3dkKk58r3vvWBsM4cnf4uvT2\n5Uh7Y9y2t/C1Puerr75i6dKlPProo9xwww39buNFxNDcHJGWlubz/k2bNjF37lzUajVJSUmMGDGC\ngoICpkyZ0scWnj8ajYbMzEwyMzN54IEHEEWRhoYGdu3axc6dO/nLX/5CS0uLR1ciJyeHESNGAG6H\nLaUlLrRINxALZReKd3Tb3fJRqdDp3Y3h3bZ2uiWhfZ1y8V6fExAQgMViYcWKFVRWVvLRRx/1mCzk\n5s2bmT9/Pk6nk3vuuYfHHnusR573YmJQO93TUVlZ2cnBxsfHYzQa+9GiC0cQBMLDw7n66qu5+uqr\nATrpSqxbt+60uhLS7rRzjdAkh6JQKAgICBhUVwq+6KkR3q6OWBKB916JJOkY9LYcY9f1OSqVioKC\nAh577DHuv/9+br311h773JxOJw888ADbtm0jLi6OrKwsZs+ezejRo3vk+S8WBrzTzc3Npbq6+pT7\nn3rqKa655pqzfp7BHp35QqlUkp6eTnp6OnffffcpuhJvvPEGNTU1JCQkeJzw2LFjEQTBZ4QmRcXe\nyzqHQhUfOqdHuotuzxXpxKVQKDzvVddxW18nvQvND3uvzzEYDNhsNv74xz/y/fff88477zBs2LAe\ne40ABQUFjBgxwiPtePPNN7Np0ybZ6Z4jA97pfvbZZ+f8N3FxcZSXl3tuV1RU9Pk+qf5AEAQMBgPT\npk1j2rRpQGddiffee4/ly5d7dCUmT57MlClTiI6O9lxyS2vcFQoFWq0WhULhWXc0GOmv9IggCB7H\nqtFoPLZ4t6x1dHScl8azr8GNffv2sWDBAm655RZWr17dK1clRqORhIQEz+34+Hh27drV48cZ6gx4\np3u2eBcEZ8+ezbx581iwYAFGo5FDhw6RnZ3dj9b1HwqFguTkZJKTk5k3b94puhIrVqygrKwMjUZD\nQ0MD48aNY+3atWg0GpxOZ6cIrbeKdL2Fdx/xQEiP+MoPe3ekSD3CZxqY8V6fYzAYcDgcrFmzhh07\ndrB+/XpSU1N71X6ZC2dQO92NGzfy4IMPUl9fz9VXX83EiRP59NNPSU9P58YbbyQ9PR2VSsWLL74o\nf2FOIggCfn5+XHLJJVxyySWAW9kpLy+PuXPnotfr+fWvf017eztpaWmeIp2kK3E2jqG/6SnBnb5A\noVCcNi0h9Q9LbWvgdtKNjY0kJCRQWlrK/PnzmTVrFlu3bu31jpKuV5Dl5eXEx8f36jGHIoO6ZWww\nsGLFCv7+978TEREBuPuHr7zyyn62qjOfffYZ48aN61ThPpOuRFZWFllZWRgMBo8K2EBpo/KOBIfC\nCC/81JkgpX3mzp1Lfn4+arWaOXPmcNVVVzF9+nSCg4N71Q6Hw8GoUaPYvn07sbGxZGdn8+abb8o5\nXd8MzT7dwcDjjz+OwWBgwYIF/W3KBdGdrkROTg5paWkoFAqfSyu9R217y76hJFADviUly8rKePDB\nB7nkkku49NJL2bNnDwUFBTz55JOMGzeu12369NNPPS1jd9999xkVwZYvX05oaCgPPfQQAEuWLCEq\nKooHH3yw1+0cAMhOt78YQqLMpyDpSkjR8P79+1EqlYwfP97jiCMiInp9usu7R3UoTMnBqetzAF57\n7TVef/11nn/+ebKysvrZwu4pKyvjuuuuo6ioCJfLxciRIyksLCQkJKS/TesLhuZwxGAhLy+P1157\njczMTJ599tlevwzsKxQKBampqaSmpnLbbbchiiLt7e0eXYlFixZRWVlJdHQ0mZmZZGdnM378eM+K\nGKvVisvlOu8Nzd4TWFKP6mDHV3RbXV3NQw89xOjRo/nPf/7jWS800ElMTCQsLIy9e/dSXV3NpEmT\nLhaHe0bkSLcHOF0v8cqVK5kyZYonn7t06VKqqqp45ZVX+trEfqM7XYns7GwSExM7bYjobqhgKGpA\nQOdeYr1ejyAIbNiwgRdffJFnnnmGn/3sZ4Pudb799tt888031NTUcMcddwy4ekYvIqcXBgLHjx/n\nmmuuYf/+/f1tSr9is9koLi5m165dHl2JoKAgjxPOzMz0qSshRcGSIthQim67Tso1NDSwYMECIiMj\nefrppzEYDP1t5nlht9sZO3YsTqeTQ4cODbqTxgUgpxf6C2nTKbhb3DIyMvrZov5Ho9F4OiB86Ur8\n9a9/9ehKSJrDw4cPZ/fu3YwaNcojTmO1WjvpDw/GH7T3+hx/f38UCgUff/wxa9asYeXKleTm5g7K\n1yWhVqu54oorCAkJGdSvoyeRI91e5rbbbmPv3r0IgkBycjIvv/xyj4mPDGW8dSW2bNnC9u3biYiI\nYNasWZ6R5pCQkFOKdD29obm38LU+p6WlxSMg8/zzzw+J/KfL5WLy5Mls2LCB4cOH97c5fYmcXpAZ\nnNTX1zNmzBgWLVrEHXfc4Zmk27VrF9XV1QwbNqyTroRCofDkh89nxLYv8LU+54svvmDFihUsXryY\nOXPmDNiTxblQUlLCNddcw3XXXceaNWv625y+Rna6Mm4GozSfyWTy2fHhrSuRn59PcXExoiiSkZHh\nSUvExsaetkjna0Nzb+JLw7e9vZ2lS5fS0NDAiy++6Cm69iSDYUBnCCI7XRn3JfuoUaM6SfMNpYmi\nrroS+fn5lJWVER4e7skhT5o0Ca1W67NI59073NP4Wp+Tn5/P4sWLeeihh5g3b16vOf+hMqAzyJAL\naTJDX5rPl66EKIpUV1eTn5/Pjh07WLt2bSddiezsbFJSUjwdBN6TdD21J817fY5er8dqtbJy5UpK\nS0vZuHFjnyjgdRNcyfQhstO9iLgYpfkEQSAmJoY5c+YwZ84coLOuRF5eHqWlpej1eiZPnkx2djZZ\nWVkEBgaeIjhzrkU6X8Mbe/fuZeHChdx5552sWbOmz3LMQ3VAZzAiO92LiKFQnOkJVCoV48ePZ/z4\n8fzud787RVfilVde6aQrkZ2dzejRoz26Er7W83RNS3Rdn+NwOFi1ahX5+fm8/vrrPV7JP9OAzn33\n3ceyZcsA94DOwoULL6oBnYGG7HQvImRpPt8IgkBwcDAzZszwbI12uVwcPnzYs4Fj3759KJVKJkyY\n0ElXwuVyefqFpSKdlCvWaDTodDp+/PFH5s+fz3XXXcfmzZt7RYLxbMX+77nnnnPauCLT88iFtIsI\nWZrv/OmqK7Fr1y6MRiPR0dGeIp3T6aSmpoYrr7wSk8lEZmYmqamp1NfX88gjj3DDDTcQGxvb57Z7\nD+g899xzFBYW8sYbb/S5HRcZcveCjJtzkeaTOTOSrsQXX3zB2rVrOXLkCJdddhlxcXEkJiaybds2\n0tPTiYiIoLCwkKKiIo4ePepRDesr5AGdfkF2ujIyvcXy5cs5duwYzz//PP7+/hQXF/PPf/6T3Nzc\nTpfyg3nXnMw5Izvdi4XCwkLuueceCgoKcDgc5OTk8Pbbb5Oent7fpp0VSUlJBAYGolQqUavVFBQU\n9LdJ3SLpP8jIeCE73YuJpUuX0tHRgcViISEhYVBMnUkkJydTVFREaGhof5siI3MhyE73YsJut3vk\nEXfu3DmoLmmTk5PZvXs3YWFh/W2KjMyFcNofXf+rf8j0OPX19ZjNZtra2jyi2IMFQRCYPn06mZmZ\nrFu3rr/NkZHpceRIdwgye/Zs5s2bx9GjR6mqqiIvL6+/TTprpPamuro6cnNzycvLY+rUqf1tlozM\nuSJHuhcLr732GlqtlptvvplFixZRWFjIF1980d9mnTVSP2lERARz5swZFIU0GZlzQY50ZQYM7e3t\nOJ1ODAYDZrOZGTNmsHz5cs+UmIzMIEKOdGUGPjU1NUydOpUJEyaQk5PDrFmzhrzDfeeddxgzZgxK\npZI9e/Z0emzVqlWkpqaSlpbG1q1b+8lCmZ5G1l6QGTAkJyezd+/e/jajT8nIyGDjxo3ce++9ne4v\nKSnhrbfeoqSkBKPRyPTp0yktLR0Qmy9kLgz5E5SR6Ya77rqLqKioTktFGxsbyc3NZeTIkcyYMQOT\nyXRez52WlsbIkSNPuX/Tpk3MnTsXtVpNUlISI0aMkPPbQwTZ6crIdMOdd97J5s2bO923evVqcnNz\nKS0t5Re/+AWrV6/u0WNWVlZ2UoCLj4/HaDT26DFk+gfZ6crIdMPUqVNP2cz7wQcfcPvttwNw++23\n8/7775/273Nzc8nIyDjl34cffnhOdgymIReZ0yPndGVkzoOamhqPUldUVBQ1NTWn/b9nq3XrTVft\n44qKij5Z6yPT+3TXMiYjIwMIgpAEfCiKYsbJ202iKIZ4Pd4oiuJ5C0YIgvA58AdRFItO3k4H3gCy\ngThgGzBClH+wgx45vSAjc37UCIIQDSAIQgxQez5PIgjCHEEQyoEpwMeCIHwKIIpiCfA2UAJ8Cvy3\n7HCHBnKkKyNzFviIdP8ENIii+LQgCIuAYFEUF/WjiTKDBNnpysh0gyAIbwKXA+FADbAM2IQ7Eh0G\nHAduFEXx/PrGZC4qZKcrIyMj04fIOV0ZGRmZPkR2ujIyMjJ9yP8HJDrcHDa8ujsAAAAASUVORK5C\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x3aa46d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.mplot3d import Axes3D\n",
    "from matplotlib import cm\n",
    "\n",
    "def f(x, y):\n",
    "    # sinc 函数\n",
    "    r = np.sqrt(x ** 2 + y ** 2)\n",
    "    result = np.sin(r) / r\n",
    "    result[r == 0] = 1.0\n",
    "    return result\n",
    "\n",
    "x_ticks = np.linspace(-10, 10, 51)\n",
    "y_ticks = np.linspace(-10, 10, 51)\n",
    "\n",
    "x, y = np.meshgrid(x_ticks, y_ticks)\n",
    "\n",
    "z = f(x, y)\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "ax.plot_surface(x, y, z,\n",
    "                rstride=1, cstride=1,\n",
    "                cmap=cm.YlGnBu_r)\n",
    "ax.set_xlabel('x')\n",
    "ax.set_ylabel('y')\n",
    "ax.set_zlabel('z')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "事实上，`x, y` 中有很多冗余的元素，这里提供了一个 `sparse` 的选项： "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "x_ticks = np.linspace(-1, 1, 5)\n",
    "y_ticks = np.linspace(-1, 1, 5)\n",
    "\n",
    "x, y = np.meshgrid(x_ticks, y_ticks, sparse=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-1. , -0.5,  0. ,  0.5,  1. ]])"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-1. ],\n",
       "       [-0.5],\n",
       "       [ 0. ],\n",
       "       [ 0.5],\n",
       "       [ 1. ]])"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "在这个选项下，`x, y` 变成了单一的行向量和列向量。\n",
    "\n",
    "但这并不影响结果："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Miniconda\\lib\\site-packages\\IPython\\kernel\\__main__.py:9: RuntimeWarning: invalid value encountered in divide\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0xba147f0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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jRzNnzpyE3V+fJF0FXSVDhWybmprCZNuRn7Or2gUK2Xq9XiwWS5tleLqjj+D3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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x3a1ab38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "x_ticks = np.linspace(-10, 10, 51)\n",
    "y_ticks = np.linspace(-10, 10, 51)\n",
    "\n",
    "x, y = np.meshgrid(x_ticks, y_ticks, sparse=True)\n",
    "\n",
    "z = f(x, y)\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "ax.plot_surface(x, y, z,\n",
    "                rstride=1, cstride=1,\n",
    "                cmap=cm.YlGnBu_r)\n",
    "ax.set_xlabel('x')\n",
    "ax.set_ylabel('y')\n",
    "ax.set_zlabel('z')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`meshgrid` 可以设置轴排列的先后顺序：\n",
    "- 默认为 `indexing='xy'` 即笛卡尔坐标，对于2维数组，返回行向量 `x` 和列向量 `y`\n",
    "- 或者使用 `indexing='ij'` 即矩阵坐标，对于2维数组，返回列向量 `x` 和行向量 `y`。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ogrid , mgrid"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Matlab**中有 `meshgrid` 的用法："
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "    meshgrid(-1:.5:1, -1:.5:1)\n",
    "\n",
    "**Numpy**的 `meshgrid` 并不支持这样的用法，但我们可以使用 `ogrid / mgrid` 来实现类似这样的用法。\n",
    "\n",
    "`ogrid` 与 `mgrid` 的区别在于：\n",
    "- `ogrid` 相当于 `meshgrid(indexing='ij', sparse=True)`\n",
    "- `mgrid` 相当于 `meshgrid(indexing='ij', sparse=False)`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "x, y = np.ogrid[-1:1:.5, -1:1:.5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-1. ],\n",
       "       [-0.5],\n",
       "       [ 0. ],\n",
       "       [ 0.5]])"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-1. , -0.5,  0. ,  0.5]])"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "注意：\n",
    "- 这里使用的是中括号\n",
    "- **Matlab** 使用的是 `start:step:end` 的表示，**Numpy** 使用的是 `start:end:step` 的表示\n",
    "- 这里的结果不包括 `end` 的值\n",
    "\n",
    "为了包含 `end` 的值，我们可以使用这样的技巧："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "x, y = np.ogrid[-1:1:5j, -1:1:5j]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([[-1. ],\n",
       "        [-0.5],\n",
       "        [ 0. ],\n",
       "        [ 0.5],\n",
       "        [ 1. ]]), array([[-1. , -0.5,  0. ,  0.5,  1. ]]))"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x, y"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们在 `step` 的位置传入一个复数 `5j` ，表示我们需要一个 `5` 个值的数组，此时返回值就会包含 `end` 的值。\n",
    "\n",
    "重复之前的画图："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Miniconda\\lib\\site-packages\\IPython\\kernel\\__main__.py:9: RuntimeWarning: invalid value encountered in divide\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.text.Text at 0x9e34278>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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jRzNnzpyE3V+fJF0FXSVDhWybmprCZNuRn7Or2gUK2Xq9XiwWS5tleLqjj+D3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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x99de780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# exchange here\n",
    "y, x = np.ogrid[-10:10:51j, -10:10:51j]\n",
    "\n",
    "z = f(x, y)\n",
    "\n",
    "fig = plt.figure()\n",
    "ax = fig.add_subplot(111, projection='3d')\n",
    "ax.plot_surface(x, y, z,\n",
    "                rstride=1, cstride=1,\n",
    "                cmap=cm.YlGnBu_r)\n",
    "ax.set_xlabel('x')\n",
    "ax.set_ylabel('y')\n",
    "ax.set_zlabel('z')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "这里，我们交换了 `x, y` 输出值的顺序。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## r`_` , c`_`"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "我们可以使用 `r_ / c_` 来产生行向量或者列向量。\n",
    "\n",
    "使用切片产生："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0. ,  0.1,  0.2,  0.3,  0.4,  0.5,  0.6,  0.7,  0.8,  0.9])"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.r_[0:1:.1]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "复数步长制定数组长度："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.  ,  0.25,  0.5 ,  0.75,  1.  ])"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.r_[0:1:5j]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "连接多个序列，产生数组："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([  3.,  22.,  11.,   4.,  15.,   6.])"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.r_[(3,22,11), 4.0, [15, 6]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "列向量："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1. ],\n",
       "       [ 1.5],\n",
       "       [ 2. ],\n",
       "       [ 2.5],\n",
       "       [ 3. ]])"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.c_[1:3:5j]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## ones , zeros"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```python\n",
    "ones(shape, dtype=float64)\n",
    "zeros(shape, dtype=float64)\n",
    "```\n",
    "\n",
    "产生一个制定形状的全 `0` 或全 `1` 的数组，还可以制定数组类型："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.,  0.,  0.])"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.zeros(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1.,  1.,  1.],\n",
       "       [ 1.,  1.,  1.]], dtype=float32)"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.ones([2,3], dtype=np.float32)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "产生一个全是 `5` 的数组："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 5.,  5.,  5.],\n",
       "       [ 5.,  5.,  5.]])"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.ones([2,3]) * 5"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## empty"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "    empty(shape, dtype=float64, order='C')\n",
    "\n",
    "也可以使用 `empty` 方法产生一个制定大小的数组（数组所指向的内存未被初始化，所以值随机），再用 `fill` 方法填充："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.03412165,  0.05516321])"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.empty(2)\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 5.,  5.])"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a.fill(5)\n",
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "另一种替代方法使用索引，不过速度会稍微慢一些："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 5.,  5.])"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a[:] = 5\n",
    "a"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## empty`_`like, ones`_`like, zeros`_`like"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "    empty_like(a)\n",
    "    ones_like(a)\n",
    "    zeros_like(a)\n",
    "\n",
    "产生一个跟 `a` 大小一样，类型一样的对应数组。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0. ,  2.5,  5. ,  7.5])"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "a = np.arange(0, 10, 2.5)\n",
    "a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.,  0.,  0.,  0.])"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.empty_like(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 0.,  0.,  0.,  0.])"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.zeros_like(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ 1.,  1.,  1.,  1.])"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.ones_like(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## identity"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "    indentity(n, dtype=float64)\n",
    "产生一个 `n` 乘 `n` 的单位矩阵："
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1.,  0.,  0.],\n",
       "       [ 0.,  1.,  0.],\n",
       "       [ 0.,  0.,  1.]])"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.identity(3)"
   ]
  }
 ],
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